CN115759569A

CN115759569A - Scheduling method and electronic equipment

Info

Publication number: CN115759569A
Application number: CN202211296661.4A
Authority: CN
Inventors: 干士; 聂鹏鹤; 徐加力; 李雨潼
Original assignee: Honor Device Co Ltd
Current assignee: Honor Device Co Ltd
Priority date: 2022-10-21
Filing date: 2022-10-21
Publication date: 2023-03-07
Anticipated expiration: 2042-10-21
Also published as: CN115759569B

Abstract

The application provides a scheduling method and electronic equipment, and relates to the technical field of data processing. First, the electronic device may create a scheduling planning model based on input variables, decision variables, scheduling constraints, and scheduling objectives set by the user. The scheduling planning model can utilize the constraint conditions and the input variables in the scheduling planning model to constrain the decision variables to obtain a plurality of variable values of the decision variables, and selects the optimal variable value from the plurality of variable values of the decision variables so as to determine the scheduling result according to the optimal variable value. Then, when a user needs to obtain a scheduling result of a product, the electronic device can determine the corresponding scheduling result by using the scheduling planning model, so that the scheduling result can be quickly obtained, the determination efficiency of the scheduling result is improved, and the stability of the scheduling result is high.

Description

Scheduling method and electronic equipment

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a scheduling method and an electronic device.

Background

In a development stage before a product (such as a mobile phone) is marketed, for example, when a marketing plan of the product is made, a production line resource of an available manufacturing supplier needs to be combined, and a production scheduling condition of a production line (referred to as a production line) is estimated to obtain a production scheduling result, wherein the production scheduling result comprises a forward result or a reverse result. For example, the forward ranking results are obtained by predicting the capacity of future products on the market in advance. For example, the production line resource allocation is estimated based on the capacity of the future products after being marketed, and the inverted result is obtained. The related personnel can use the positive discharging result or the reverse discharging result to perform related processing, such as purchasing required raw materials in advance, starting a corresponding production line according to the positive discharging result or the reverse discharging result, and the like.

At present, when estimating the scheduling condition of a production line, related personnel (such as a salesman) generally perform scheduling simulation by experience. Specifically, related personnel adjust the raw material input and capacity conditions of each production line through repeated trial calculation to determine the optimal raw material input and capacity conditions of each production line, so that corresponding scheduling results are obtained.

However, when the scheduling result is determined manually, the time required to determine the scheduling result is long, and the scheduling result determination efficiency is low. In addition, in the process of manually determining the scheduling result, a large amount of trial adjustment needs to be performed based on the experience of related personnel, and problems are easy to occur in the trial adjustment process, so that the reliability of the scheduling result is low.

Disclosure of Invention

In view of this, the present application provides a scheduling method and an electronic device, which improve the determination efficiency and reliability of the scheduling result.

In a first aspect, the present application provides a scheduling method, in which an electronic device obtains product production information corresponding to a product to be scheduled, where the product production information includes one or more of a climbing curve of at least one production line, production line adding limit information, product time information, total target energy, and material supply information. The climbing curve of the at least one production line comprises at least one of a productivity climbing curve, a yield climbing curve and a passing rate climbing curve of each production line in the at least one production line; the production line adding limit information comprises the earliest starting time of each production line and/or the starting time difference between the production lines in at least one production line; the product time information includes at least one of a production cycle, a prospect and a transportation cycle of the product to be scheduled; the material supply information indicates a supply quantity of at least one raw material at the prospect;

the electronic equipment analyzes the product production information and determines the variable value of a preset input variable;

the electronic equipment performs constraint calculation on a preset decision variable based on a preset scheduling constraint condition and a variable value of the input variable to obtain a scheduling result, wherein the scheduling result comprises a positive scheduling result or a reverse scheduling result; the preset decision variable indicates a service element to be solved, and the service element indicates at least one of planned capacity, planned feeding quantity, planned starting time, planned yield and planned passing rate of the production line; the preset scheduling constraint condition is used for constraining the value of the preset decision variable based on the variable value of the input variable, and the preset scheduling constraint condition meets the actual production attribute of a production line of the product to be scheduled.

In the method and the device, the electronic equipment can automatically restrict the value of the input decision variable by utilizing the preset scheduling restriction condition and the variable value of the preset input variable, so that the scheduling result according with the actual production condition is obtained, manual trial and error adjustment is not needed, the automatic determination of the scheduling result is realized, the determination efficiency of the scheduling result is improved, and the stability of the scheduling result is ensured. Meanwhile, the electronic equipment can output a positive-ranking result and a reverse-ranking result by utilizing the preset scheduling constraint condition, the preset input variable and the preset decision variable, so that the acquisition requirements of different scheduling results of a user are met.

In one possible design, the determining the variable value of the preset input variable is actually determining the variable value of the input variable in the scheduling planning model; the scheduling plan also comprises decision variables and scheduling constraint conditions; the scheduling planning model is used for performing constraint calculation on the decision variable by using the scheduling constraint condition and the variable value of the input variable to obtain a scheduling result;

the electronic equipment inputs the variable value of the input variable into the scheduling planning model and obtains the scheduling result of the product output by the scheduling planning model, wherein the scheduling result comprises a positive scheduling result or a reverse scheduling result.

In the application, the electronic equipment can automatically determine the corresponding scheduling result by using the scheduling planning model, and the specific solving process of the scheduling result is not needed, so that the scheduling result can be quickly obtained, and the determination efficiency of the scheduling result is improved. And the scheduling planning model is an accurate algorithm, so that the scheduling result can accord with the global optimum, and the reliability of the determined scheduling result is ensured, so that related personnel can accurately follow up related plans based on the scheduling result. And the coupling between the scheduling constraint conditions in the scheduling planning model is low, and the scheduling planning model can select a proper scheduling constraint condition and a scheduling result to be output from the scheduling constraint conditions according to the actual business requirements, so that the scheduling constraint condition and the scheduling result can be flexibly switched based on the business requirements, and different scheduling result requirements of users are met.

In one possible design, the product production information includes an earliest start time of each production line, and the input variables include pre-production line variables of the production lines;

the electronic device may be determined in the following two ways when determining the variable value of the pre-production line variable of the production line based on the earliest start time of each production line.

In one embodiment, the electronic device may sort the production lines based on the earliest starting time of the production lines to obtain an arrangement order of the production lines; for each production line, the electronic device determines the serial number of the front production line of the production line from the arrangement sequence of the production lines, and takes the serial number of the front production line of the production line as the variable value of the front production line variable of the production line.

In the application, the front production line of the production line is determined, so that the scheduling planning model can utilize the front production line of the production line to restrict the starting condition of the production line, and the problem of starting the production line is avoided.

In another embodiment, the electronic device may sort the production lines based on the earliest starting time of the production lines to obtain an arrangement order of the production lines;

the electronic equipment generates a tree structure diagram of the production line based on the arrangement sequence of the production line, and nodes in the tree structure diagram indicate the production line;

for each node in the tree structure diagram, the electronic device obtains the number of the production line indicated by the previous node of the node, and uses the number of the production line indicated by the previous node as the variable value of the preposed production line variable of the production line indicated by the node.

Wherein, the weight of the connecting edge between the adjacent nodes in the tree structure chart is the starting time difference between the adjacent nodes.

In the present application, by constructing the tree structure diagram of the production line, the related information (such as the variable value of the pre-production line variable of the production line) can be quickly obtained and determined.

In one possible design, the production scheduling constraint condition includes one or more of a numerical constraint condition, a material balance constraint condition, a reverse-scheduling climbing constraint condition, a production line feeding constraint condition and a production line capacity constraint condition;

wherein, the value constraint condition is used for constraining the value range of the decision variable; the material balance constraint condition is used for constraining the total usage amount of the raw materials not to be larger than the accumulated input amount of the raw materials; the inverted climbing constraint condition is used for constraining the total quantity of products delivered by a production line to be not less than the total target energy; the feeding constraint condition of the production line is used for constraining the starting time of the production line;

the production line capacity constraint condition is used for constraining the production line capacity, the produced good product quantity, the delivered good product quantity and the like.

In the method and the device, the scheduling constraint condition used for determining the scheduling result is set based on the actual production situation, so that the finally determined scheduling result is more reliable and accurate.

For example, the scheduling constraints corresponding to different scheduling results may be different; for example, the scheduling constraint condition corresponding to the positive scheduling result may include one or more of a numerical constraint condition, a material balance constraint condition, a production line material feeding constraint condition, and a production line capacity constraint condition; the scheduling constraint condition corresponding to the inverted result may include one or more of a numerical value constraint condition, a material balance constraint condition, an inverted climbing constraint condition, a production line feeding constraint condition, and a production line capacity constraint condition.

In a possible design, the operating the scheduling planning model to output the scheduling result of the product includes:

when receiving the selection operation of a user on a target scheduling result option in a first interface, the electronic equipment responds to the selection operation of the target scheduling result option, takes the target scheduling result option as input, and operates the scheduling planning model to output a scheduling result corresponding to the target scheduling result option; the target yield result option indicates a positive or negative result.

In the method, the user can select the scheduling result required to be output by the scheduling planning model on the electronic equipment according to the scheduling requirement, so that the scheduling planning model can select a proper scheduling constraint condition to constrain the decision variable to obtain a corresponding scheduling result, the flexible switching between the scheduling constraint condition and the scheduling result is realized, the electronic equipment also supports the flexible switching of the scheduling result, namely, the user can obtain a positive scheduling result by using the electronic equipment, and the user can obtain a reverse scheduling result by using the electronic equipment.

In a possible design, the inverted result includes an inverted target, and the inverted target includes one or more of the latest starting time of the earliest production line, the latest starting time of all production lines, the least number of the started production lines, the latest starting time of the earliest production line, and the least number of the started production lines;

the above-mentioned operation of this scheduling planning model outputs the scheduling result of this product, including:

the electronic equipment receives the selection operation of a user on a first inverted target option in a second interface; and the electronic equipment responds to the selection operation of the first inverted target option, takes the first inverted target option as an input, runs the scheduling planning model and outputs an inverted result corresponding to the target scheduling result option, wherein the inverted result comprises an inverted target corresponding to the first inverted target option.

In the application, the user can select the inverted target required to be output by the scheduling planning model on the electronic equipment according to the scheduling requirement, so that the scheduling planning model can select a proper scheduling constraint condition to constrain a decision variable to obtain a corresponding inverted target, the flexible switching of different inverted targets is realized, the electronic equipment also supports the flexible switching of the inverted targets, and the user can obtain different inverted targets by utilizing the electronic equipment.

In a possible design, the decision variables include a planned input quantity variable of a raw material of an i-th production line on a k-th day, a planned capacity variable of the i-th production line on the k-th day, a planned delivery quantity variable of the i-th production line on the k-th day, an actual capacity upper limit variable of the i-th production line on the k-th day, at least one of a start-up variable of the i-th production line on the k-th day, a non-start-up variable of the i-th production line on the k-th day, a planned earliest start-up time variable of the i-th production line, a virtual start-up time variable of the i-th production line, a planned yield variable of the i-th production line on the k-th day, and an accumulated consumption variable of a j-th raw material on the k-th day, where i, k, j-th production line is a non-negative integer, the i, k-th production line is any one production line, the k-th day is any day in the planning period, and the j-th raw material is one raw material in the at least one raw material.

In the application, the decision variables in the scheduling planning model are set based on the actual production situation, such as the actual capacity upper limit variable is set in a climbing state based on the capacity of the production line, so that the scheduling result output by the scheduling planning model is more reliable and accurate.

In a second aspect, the present application provides an electronic device, which is a first electronic device, comprising a display screen, a memory, and one or more processors; the display screen, the memory and the processor are coupled; the display screen is for displaying images generated by the processor, the memory is for storing computer program code, the computer program code comprising computer instructions; the computer instructions, when executed by the processor, cause the electronic device to perform the method as described above.

In a third aspect, the present application provides a computer readable storage medium comprising computer instructions which, when run on an electronic device, cause the electronic device to perform the method as described above.

In a fourth aspect, the present application provides a computer program product which, when run on an electronic device, causes the electronic device to perform the method as described above.

It should be understood that, for the electronic device according to the second aspect, the computer-readable storage medium according to the third aspect, and the computer program product according to the fourth aspect, reference may be made to the advantageous effects of the first aspect and any possible design manner thereof, and details are not described here again.

Drawings

Fig. 1 is a schematic diagram illustrating an input-output result of a production line according to an embodiment of the present disclosure;

fig. 2 is a first schematic diagram illustrating a scheduling result determining process according to an embodiment of the present disclosure;

fig. 3 is a schematic hardware structure diagram of an electronic device according to an embodiment of the present application;

fig. 4 is a schematic diagram illustrating a scheduling result determining process according to an embodiment of the present application;

fig. 5 is a third schematic diagram of a scheduling result determination process provided in the embodiment of the present application;

fig. 6 is a fourth schematic diagram of a scheduling result determination process provided in the embodiment of the present application;

fig. 7 is a schematic view of a tree structure of a production line according to an embodiment of the present disclosure;

FIG. 8 is a first schematic diagram illustrating a scheduling result selection provided by an embodiment of the present application;

FIG. 9 is a second schematic diagram illustrating a selection of scheduling results according to an embodiment of the present application;

fig. 10 is a schematic diagram of a production line time constraint according to an embodiment of the present application.

Detailed Description

In the following, the terms "first", "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present embodiment, "a plurality" means two or more unless otherwise specified.

In order to better understand the aspects of the present application, terms referred to in the embodiments of the present application are described below.

(1) And (3) positive row: it can also be called a forward target, which refers to calculating the maximum capacity that can be reached by a target date based on the production line body (or called a production line) of the supplier, that is, the maximum number of products that can be produced by the production line of the supplier in the period from the production to the target date.

(2) And (4) inverted discharging: the method can also be called as an inverted target, and means that the optimal production line resource configuration is calculated based on the production line body of a supplier and taking the target date and the maximum capacity as targets. Such as the latest start time of the production line.

Wherein, the production line body can be understood as a production line.

(3) Greedy principle: the principle is that when solving a problem, the choice that seems best at the present time is always made. That is, instead of considering the global optimum, a locally optimum solution is made.

When a marketing plan of a product is formulated, the production line condition of the production line is estimated to obtain a production line result (such as a forward production result or a backward production result) by combining available production line resources of a manufacturing supplier, so that related personnel can reasonably plan the start-up rhythm of the production line by using the production line result, and the marketing and the quantity of the product are ensured. For example, capacity advance after coming into the market is predicted to obtain positive results.

The scheduling result comprises a scheduling target and a scheduling scheme. Illustratively, the yield targets include a forward target and a reverse target. The scheduling scheme represents the starting of each production line, the raw material input condition, the productivity and other conditions.

In some embodiments, when determining the scheduling result, the relevant person determines the corresponding forward scheduling result or reverse scheduling result by means of his own experience and trial calculation and adjustment repeatedly in a table (Excel) based on greedy principle to schedule one production line, and if there are remaining raw materials (i.e. materials) or the target capacity is not reached, the relevant person continues to schedule the next production line. However, the manual determination of the scheduling result is time-consuming, so that the efficiency of determining the scheduling result is low. Moreover, the scheduling result is based on the experience of the related personnel and needs to be adjusted by trial and error, so that the reliability of the determined scheduling result is low.

Since the scheduling result directly affects the formulation of the subsequent related plans (product supply and sales plan), when the reliability of the scheduling result is low, the related personnel cannot accurately formulate the related plans.

For example, when the relevant personnel manually determines the positive ranking result, when the determined positive ranking target is larger, the estimation of the maximum capacity of the product is larger, so that the formulation of sales and operation plans (S & OP) has a radical problem. Accordingly, there may be a problem of insufficient supply of the product after the product is marketed.

For another example, when the determined forward target is smaller, it indicates that the estimated maximum capacity of the product is smaller, and at this time, the forward target is not optimal, so that there is a conservative problem in the formulation of sales and operation plans (S & OP). Accordingly, after the product is marketed, the order of the product may be lost due to the small quantity of the produced product, and the product income may be affected.

For another example, when the related personnel manually determines the inversion result, when the reliability of the inversion target, that is, the resource allocation determination of the production line is low, the development planning may be inaccurate, so that the development time is insufficient, and the contract cost of the supplier may be high.

In other embodiments, in the positive scene, the relevant personnel will aggregate the trial adjustment process into corresponding rules, and implement the rules through codes. The electronic device may then run the code to automatically iterate through the loop until no raw materials remain or the production line is finished looping without a production line having been scheduled and a positive result is obtained. However, the code is still determined based on the experience of the relevant person, but the process of manual trial adjustment is changed to automatic trial adjustment, and therefore the reliability of the determined positive result may still be low. The positive result may include a positive scheme indicating raw material input and production capacity of the production line. For example, the raw material comprises raw material a, and the production line comprises company 1's production line. Referring to fig. 1, the production line of company 1 starts from startup and ends at month 5 and 13, the number of planned raw materials a to be charged is 2100 pieces (pcs), and the planned cumulative capacity of the production line of company 1 is 2100pcs.

Thereafter, after the calculation of the positive rank result, the electronic device may end the calculation of the positive rank result.

In other embodiments, in an inverted scenario, the electronic device may enumerate the production line resource configuration based on a heuristic rule to obtain a plurality of enumeration results. The production line resource allocation can comprise the number of the production lines, the production line starting time, the number of the raw materials input into the production lines, the production capacity of the production lines and the like. And finally, judging whether the feasibility of each enumeration result and the total scheduling amount reach the standard or not by the electronic equipment. And then, the electronic equipment selects a target result from the feasible and up-to-standard enumeration results based on the relevant business rules and takes the target result as an inverted result. Or, the related personnel select a target result from the feasible and up-to-standard enumeration results by virtue of own experience and take the target result as an inverted result. However, heuristic rules cannot enumerate all possible combinations, and the computational optimality is not guaranteed, resulting in lower reliability of scheduling results. And when the calculation scenes of the scheduling results are different, different rules need to be set, that is, different codes need to be corresponding, and the maintenance cost is higher. And heuristic rules have more business constraints, the realization process is complex, and the calculation efficiency of the scheduling result is reduced. By means of the service constraint and the scheduling result, flexible switching cannot be achieved, and the service mode cannot be adjusted rapidly, for example, whether a forward scheduling result or a reverse scheduling result is output cannot be selected according to requirements.

Specifically, the enumeration result includes parameter values of decision parameters, for example, a target result is selected from feasible and qualified enumeration results of planned input raw materials of the production line 1, and the target result is used as the number of inverted results, the number of produced products, and the like. As shown in fig. 2, when determining an enumeration result, the electronic device may determine a parameter value of a decision parameter based on a specific parameter value of an input parameter set by a user and a calculation rule, so as to obtain a plurality of enumeration results. Thereafter, the electronic device may determine an inversion scheme from the plurality of enumeration results, so that the electronic device may obtain a corresponding inversion result based on the inversion scheme.

Therefore, in order to solve the above problems, the present application provides a scheduling method. Firstly, the electronic device can create a scheduling planning model by using input variables, decision variables, scheduling constraint conditions and scheduling targets set by a user, and the scheduling planning model can constrain the decision variables by using the scheduling constraint conditions and the input variables in the scheduling planning model to determine a scheduling result. The scheduling constraint is determined based on the actual production conditions of the production line. The preset decision variable indicates a business element to be determined, and the business element indicates at least one of planned capacity, planned material feeding quantity, planned starting time, planned yield and planned passing rate of a production line.

The electronic device may then determine a corresponding scheduling result using the scheduling planning model. Specifically, when the user needs to determine the scheduling result of the product, product production information is input on the electronic device. The product production information is used to determine variable values for input variables of the scheduling planning model. The product production information may include at least one of a climbing curve, production line plus line limit information, target product time information, target total energy, and material supply information for each production line. The climbing curve comprises at least one of a productivity climbing curve, a yield climbing curve and a passing rate climbing curve.

The electronic device then parses the product manufacturing information to determine the variable values of the input variables.

Then, the electronic device inputs the variable value of the input variable into the scheduling planning model, so that the scheduling planning model performs solution calculation on the decision variable based on the scheduling constraint condition and the variable value of the input variable to obtain a plurality of variable values of the decision variable, namely a plurality of scheduling schemes, and determines an optimal scheduling scheme from the plurality of scheduling schemes, thereby obtaining a corresponding scheduling result based on the optimal scheduling scheme. The scheduling result comprises scheduling targets, wherein the scheduling targets comprise a positive scheduling target and a reverse scheduling target. Wherein the front row target represents the maximum delivery total of all production lines. The inverted target indicates the configuration of the production line resource. In the application, after the setup planning model is established, the electronic equipment can automatically determine the corresponding setup result by using the setup planning model, and the electronic equipment does not need to perform a specific solving process of the setup result, so that the setup result can be quickly obtained, and the determination efficiency of the setup result is improved. Moreover, because the scheduling constraint condition in the scheduling planning model is determined based on the actual production condition of the production line, and the decision variable in the scheduling planning model is also set based on the service element which needs to be concerned in the actual production, the scheduling planning model is an accurate algorithm, so that the scheduling result obtained by the electronic equipment by using the scheduling planning model accords with the global optimum, the reliability of the determined scheduling result is ensured, and relevant personnel can accurately follow up the relevant plan based on the scheduling result. The scheduling planning model can select a proper scheduling constraint condition and a scheduling target required to be output from the scheduling constraint condition according to actual business requirements, so that the scheduling constraint condition and the scheduling target can be flexibly switched based on the business requirements, namely, the flexible switching of scheduling results can be flexibly selected, and therefore the electronic equipment can support the flexible switching of the scheduling results, namely, a user can obtain a positive scheduling result by using the electronic equipment and can obtain a reverse scheduling result by using the electronic equipment, and different scheduling target requirements of the user can be met. For example, when the product production information includes the total target capacity, which indicates that the inverted result needs to be determined, the business requirement indicates that the inverted result needs to be determined, that is, the user wants to obtain the inverted result; for another example, when the product production information does not include the total target performance, indicating that a positive result needs to be determined, the business requirement indicates that a positive result needs to be determined, that is, the user wants to obtain a positive result.

The coupling between the scheduling constraints means that the scheduling constraints are independent from each other, and the association is low, that is, the addition, deletion and modification of the scheduling constraints do not affect the use of other scheduling constraints.

For example, the electronic device may be an electronic device with data calculation capability, such as a server, a desktop computer, a notebook computer, and the like, and the embodiment of the present application does not particularly limit a specific form of the electronic device.

For example, fig. 3 shows a schematic structural diagram of the electronic device 100. As shown in fig. 3, the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a Universal Serial Bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a key 190, a motor 191, an indicator 192, a camera 193, a display screen 194, a Subscriber Identity Module (SIM) card interface 195, and the like.

It is to be understood that the illustrated structure of the embodiment of the present invention does not specifically limit the electronic device 100. In other embodiments of the present application, electronic device 100 may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

Processor 110 may include one or more processing units, such as: the processor 110 may include a CPU, an Application Processor (AP), a modem processor, a Graphics Processor (GPU), an Image Signal Processor (ISP), a controller, a memory, a video codec, a Digital Signal Processor (DSP), a baseband processor, and/or a neural-Network Processing Unit (NPU), etc. The different processing units may be separate devices or may be integrated into one or more processors.

The controller may be, among other things, a neural center and a command center of the electronic device 100. The controller can generate an operation control signal according to the instruction operation code and the timing signal to complete the control of instruction fetching and instruction execution.

A memory may also be provided in processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may hold instructions or data that have just been used or recycled by the processor 110. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. Avoiding repeated accesses reduces the latency of the processor 110, thereby increasing the efficiency of the system.

In some embodiments, processor 110 may include one or more interfaces. The interface may include an integrated circuit (I2C) interface, an integrated circuit built-in audio (I2S) interface, a Pulse Code Modulation (PCM) interface, a universal asynchronous receiver/transmitter (UART) interface, a Mobile Industry Processor Interface (MIPI), a general-purpose input/output (GPIO) interface, a Subscriber Identity Module (SIM) interface, and/or a Universal Serial Bus (USB) interface, etc.

It should be understood that the connection relationship between the modules according to the embodiment of the present invention is only illustrative and is not limited to the structure of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection manners or a combination of multiple interface connection manners in the above embodiments.

The charging management module 140 is configured to receive charging input from a charger. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like.

The

antennas

1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 100 may be used to cover a single or multiple communication bands. Different antennas can also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may be multiplexed as a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 150 may provide a solution including 2G/3G/4G/5G wireless communication applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a Low Noise Amplifier (LNA), and the like. The mobile communication module 150 may receive the electromagnetic wave from the antenna 1, filter, amplify, etc. the received electromagnetic wave, and transmit the electromagnetic wave to the modem processor for demodulation. The mobile communication module 150 may also amplify the signal modulated by the modem processor, and convert the signal into electromagnetic wave through the antenna 1 to radiate the electromagnetic wave. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be disposed in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be disposed in the same device as at least some of the modules of the processor 110.

The modem processor may include a modulator and a demodulator. The modulator is used for modulating a low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used for demodulating the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then passes the demodulated low frequency baseband signal to a baseband processor for processing. The low frequency baseband signal is processed by the baseband processor and then passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to the speaker 170A, the receiver 170B, etc.) or displays an image or video through the display screen 194. In some embodiments, the modem processor may be a stand-alone device. In other embodiments, the modem processor may be provided in the same device as the mobile communication module 150 or other functional modules, independent of the processor 110.

The wireless communication module 160 may provide solutions for wireless communication applied to the electronic device 100, including Wireless Local Area Networks (WLANs) (e.g., wireless fidelity (Wi-Fi) networks), bluetooth (bluetooth, BT), global Navigation Satellite System (GNSS), frequency Modulation (FM), near Field Communication (NFC), infrared (IR), and the like. The wireless communication module 160 may be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, performs frequency modulation and filtering processing on electromagnetic wave signals, and transmits the processed signals to the processor 110. The wireless communication module 160 may also receive a signal to be transmitted from the processor 110, perform frequency modulation and amplification on the signal, and convert the signal into electromagnetic waves via the antenna 2 to radiate the electromagnetic waves.

The electronic device 100 implements display functions via the GPU, the display screen 194, and the application processor. The GPU is a microprocessor for image processing, and is connected to the display screen 194 and an application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.

The display screen 194 is used to display images, video, and the like. The display screen 194 includes a display panel. The display panel may be a Liquid Crystal Display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (active-matrix organic light-emitting diode, AMOLED), a flexible light-emitting diode (FLED), a miniature, a Micro-oeld, a quantum dot light-emitting diode (QLED), or the like. In some embodiments, the electronic device 100 may include 1 or N display screens 194, N being a positive integer greater than 1.

The electronic device 100 may implement a shooting function through the ISP, the camera 193, the video codec, the GPU, the display 194, the application processor, and the like.

The external memory interface 120 may be used to connect an external memory card, such as a Micro SD card, to extend the memory capability of the electronic device 100.

The internal memory 121 may be used to store computer-executable program code, which includes instructions. The processor 110 executes various functional applications of the electronic device 100 and data processing by executing instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. The storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required by at least one function, and the like. The storage data area may store data (such as audio data, phone book, etc.) created during use of the electronic device 100, and the like. In addition, the internal memory 121 may include a high speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, a Universal Flash Storage (UFS), and the like.

In some embodiments, the internal memory 121 may be used to store a first PSF result corresponding to the calibrated camera 193 and a second PSF result corresponding to the calibrated single lens reflex.

The electronic device 100 may implement audio functions via the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone interface 170D, and the application processor. Such as music playing, recording, etc.

The keys 190 include a power-on key, a volume key, and the like. The keys 190 may be mechanical keys. Or may be touch keys.

Indicator 192 may be an indicator light that may be used to indicate a state of charge, a change in charge, or a message, missed call, notification, etc.

The sensor module 180 may include a pressure sensor, a gyroscope sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a distance sensor, a proximity light sensor, a fingerprint sensor, a temperature sensor, a touch sensor, an ambient light sensor, a bone conduction sensor, and the like.

In order to realize the calculation of the scheduling result of the product to be marketed, the electronic equipment can create the scheduling planning model based on the integer planning model and the user configuration input variable, the decision variable and the scheduling constraint condition, so that the electronic equipment can utilize the scheduling planning model to realize the quick and accurate determination of the scheduling result.

The scheduling method provided by the embodiment of the application can be applied to an instant volume production scene, namely, can be applied to a scheduling result determination scene of various products (namely manufactured products). Illustratively, the product comprises finished products such as a mobile phone, a notebook computer and a tablet computer, material components such as a camera module and a display screen, and the like.

The scheduling method provided by the embodiment of the present application is divided into two embodiments for introduction, wherein the embodiment one is used for introducing a scheduling planning model creation part, and the embodiment two is used for introducing an application part of the scheduling planning model.

Example one

The embodiment of the application provides a scheduling method. In this embodiment, as shown in FIG. 4, the scheduling planning model includes variables, scheduling constraints, and scheduling objectives. Therefore, the electronic device needs to construct variables of the scheduling planning model, and set scheduling constraints and scheduling targets. The process of constructing the variables can be described in the following section a. The process of setting the scheduling constraint may be described in the following section b. And the setup procedure of the scheduling objective can be described as follows in section c.

a. Constructional variables

Illustratively, the variables of the scheduling planning model include input variables and decision variables. The input variables represent input parameters of the model that indicate information that needs to be input by the user. The decision variables represent the parameters to be solved, which may indicate the content of the output required by the scheduling model.

The construction process of the input variables will be described below.

The user sets input variables on the associated interface on the electronic device. The electronic device may receive a setting operation for the input variable and may obtain the input variable of the production planning model in response to the setting operation. Controls, such as text boxes and the like, exist on the relevant interface, and allow a user to set input variables.

For example, the input variables may include a production line number set I, production cycle days alpha, lead cycle days beta, a prospective date index set K, and a cumulative input variable s of the jth raw material on the kth day _jk And the earliest starting time variable e of the ith production line _i Ith production line prepositive production line variable pi _i And a variable a of the number of days of the minimum interval of starting between the ith production line and the prepositive production line of the ith production line _i I th production line in all production lines _i The upper limit variable q of the production capacity of the ith production line on the kth day _ik The yield variable w of the ith production line on the kth day _ik The throughput rate variable r of the ith production line on the kth day _ik Capacity upper limit difference variable of ith production line on two adjacent days

Yield difference variable of ith production line on two adjacent days

Passing rate difference variable of ith production line on two adjacent days

And one or more of total target energy F.

Wherein K is an element in the prospective date index set K. Each date in the prospect is represented by an index, which may be numeric and increasing or decreasing in some order. For example, the index is 0,1,2 \8230, the index is an increasing integer, and day 1 in the prospect can be represented by 0, i.e., day 0 is actually day 1 in the prospect.

For convenience of description, the date index is 0,1,2 \8230, the increasing integer is exemplified as follows, i.e., k may be 0,1,2 \8230;, the increasing integer 8230.

The throughput rate may also be referred to as Incoming Quality Control (IQC). In short, the product is lost during transport, and the pass rate indicates the proportion of the product that is not lost to all of the product transported.

The difference variable of the upper limit of the capacity of the ith production line on two adjacent days

The yield difference value of the ith production line on two adjacent days

The throughput difference of the ith production line on two adjacent days

The cumulative amount of the j-th raw material charged on the k-th day represents the cumulative amount of the j-th raw material charged on all the production lines on the k-th day. For example, the production line comprises a production line 1 and a production line 2, k is 1, the jth raw material is material A, and the cumulative input amount of the material A on the 1 st day is the sum of four values, namely the number of the material A input by the production line 1 on the 0 th day, the number of the material A input by the production line 2 on the 0 th day, the number of the material A input by the production line 1 on the 1 st day and the number of the material A input by the production line 2 on the 1 st day.

It should be understood that if the built scheduling planning model does not need to output the inverted result, the user does not need to set the total target performance F.

The construction process of the input variables is described above, and the construction process of the decision variables will be described below.

The user sets decision variables on the relevant interface on the electronic device. The electronic equipment can receive the setting operation of the decision variable, and can respond to the setting operation of the decision variable of the user to determine the decision variable of the scheduling planning model so as to construct the business element to be subjected to model decision, namely the scheduling target, into the decision variable in a parameter mode, and the variable value of the decision variable is a specific numerical value. Controls, such as text boxes, list options and the like, exist on the relevant interface, and can be used for setting decisions by a user.

Illustratively, the decision variables include the planned input of raw material x for the ith production line on the kth day _ik The planned capacity variable y at day k at the ith birth _ik And the scheduled delivery quantity variable f of the ith production line on the kth day _ik The actual upper limit value variable c of the ith production line on the kth day _ik The ith production line starts a variable p on the kth day _ik I th production line has no start variable v on k th day _ik And the earliest planned starting time variable d of the ith production line _i And the virtual starting time variable g of the ith production line _i And the planned output yield variable l of the ith production line on the kth day _ik And a cumulative consumption variable m of the jth raw material on the kth day _ik At least one of (a).

Wherein, the above p _ik May be 0 and 1. For example, when the ith line has been started on day k, the p _ik The value of (1) may be 1, i.e. the value of the variable of the i-th production line start-up variable at the k-th day is 1.

When the ith line is not started on the kth day, p is _ik Can be 0, i.e. the value of the variable of the i-th production line start-up variable on the k-th day is 0.

The planned capacity in the planned capacity variables refers to the planned good product capacity, i.e., the quantity of the planned good products. The scheduled delivery amount in the scheduled delivery amount variable is set to the scheduled delivery good data, that is, the number of scheduled production good.

The upper limit value of the production capacity is actually the maximum number of products produced by the production line, and the products comprise good products and defective products.

V above _ik The values of (b) may be 1 and 0. For example, when the ith line is not started on the kth day, v is _ik The value of (1) may be 1, i.e. the variable value of the i-th production line non-activated variable at the k-th day is 1.

When the ith production line has been started on the kth day, the v _ik The value of (b) may be 0, i.e., the variable value of the i-th production line non-activated variable at the k-th day is 0.

The variable value of the virtual start time variable of the ith production line = the sum of the variable value of the earliest start time variable di of the ith production line and the virtual delay time. In some scenarios, it may happen that the start-up time of the production line is not within the expectation, and therefore, the start-up time of the production line needs to be represented by the virtual start-up time, so as to ensure normal calculation of the scheduling result.

The above-mentioned earliest starting time d _i The value of the variable (b) is any element in the aforementioned expecting date index set K. For example, the expectation is 12 months No. 1 to 30 when d _i When the variable value of (a) is 0, it indicates that the i-th production line is started at 12 months 1. When d is _i When the variable value of (1) indicates that the i-th production line is started at 12 months 2, and so on, and when the variable value of (di) is 29, indicates that the i-th production line is started at 12 months 30.

b. And setting scheduling constraint conditions.

The user enters the scheduling constraints on the associated interface on the electronic device. The electronic equipment can respond to the input operation of the constraint condition of the user, and the constraint condition input by the user is used as the scheduling constraint condition of the scheduling planning model, so that the electronic equipment can utilize the scheduling constraint condition to constrain the decision variable, and finally, the obtained scheduling result conforms to the basic business rule.

Wherein, the scheduling constraint condition is a linear inequality. The scheduling constraints may correspond to scheduling objectives. Illustratively, the scheduling constraint condition corresponding to the positive scheduling result includes at least one of a numerical value constraint condition, a material balance constraint condition, a production line feeding constraint condition and a production line capacity constraint condition.

The scheduling constraint condition corresponding to the inverted target may include at least one of a numerical value constraint condition, a material balance constraint condition, an inverted climbing constraint condition, a production line feeding constraint condition, and a production line capacity constraint condition.

The numerical constraint condition is used for limiting the value range of the decision variable. Specifically, the numerical constraint may include at least one of a non-negative constraint, an integer constraint, and a value constraint.

In one example, the numerical constraints include non-negative constraints. The non-negative constraint condition indicates that the variable values of the first decision variables all need to be non-negative. In particular, the non-negative constraint condition may be a first decision variable

The first decision variable I belongs to I, J belongs to J, and K belongs to K.

Wherein the first decision variable comprises x _ik ，y _ik ，f _ik ，c _ik ，l _ik ，d _i ，g _i ，m _jk At least one of (a). For example, when the first decision variable comprises x _ik ，y _ik ，f _ik ，c _ik ，l _ik ，d _i ，g _i ，m _jk When the non-negative constraint condition includes x _ik ，y _ik ，f _ik ，c _ik ，l _ik ，d _i ，g _i ，

j∈J，k∈K。

In another example, the numerical constraints may include integer constraints. The integer constraint condition indicates that the variable values of the second decision variable need to be integers.

In particular, the integer constraint may be a second decision variable

The second decision variable I ∈ I, J ∈ J, K ∈ K, and Z is an integer set.

The second decision variable may comprise x _ik ，y _ik ，f _ik ，c _ik ，d _i ，g _i ，m _jk At least one of (a). For example, the second decision variable may comprise x _ik ，y _ik ，f _ik ，c _ik ，d _i ，g _i ，m _jk When, the integer constraint can be x _ik ，y _ik ，f _ik ，c _ik ，d _i ，g _i ，

j∈J，k∈K。

In another example, the numerical constraints may include value constraints. The value constraint condition indicates that the variable value of the third decision variable needs to be a specified value.

Specifically, the value constraint condition may be a third decision variable

The variable value of the third decision variable belongs to I, K belongs to K { | K | }, i.e., the variable value of the third decision variable needs to be limited to 1 or 0.

Wherein the third decision variable may comprise p _ik And/or v _ik 。

The material balance constraint condition is used for constraining the total usage amount of the raw materials not to be larger than the input total amount of the raw materials so as to avoid the error condition that the usage amount of the raw materials is larger than the supply amount.

In one example, the material balance constraint can include

That is, for each raw material, the cumulative consumption of that raw material per day is the sum of the cumulative consumption of that raw material on the previous day and the planned daily input of that raw material. Wherein the daily input amount of the raw materials is the sum of the input amounts of the raw materials of each production line.

In another example, the material balance constraint can include

K is equal to K, s _jk Represents the cumulative input variable of the j material in k days _ik Represents the cumulative consumption variable of the j-th raw material on the k-th day. M is _jk ≤s _jk The cumulative consumption of the jth raw material on the kth day is not larger than the cumulative input of the jth material on the kth day.

It is understood that when k =0, the day 0 is not the previous day, and therefore, the cumulative consumption of the raw material amount on the previous day may be 0, that is, the cumulative consumption of the raw material on the day 0 is the sum of the planned input amounts on the day 0.

The above-mentioned inverted ramp constraint represents a total energy bottom-preserving constraint, that is, the total number of products that can be delivered from the beginning to the end of the expectation for each production line needs to be not less than the target total energy. Specifically, the constraint condition of the inverted row climbing comprises sigma _k∈K ∑ _i∈I f _ik ≥F。

The production line feeding constraint condition is used for constraining the starting time of the production line, and may include one or more of a production line running state constraint condition, a production line starting state constraint condition, a production line earliest starting time constraint condition, a production line starting time constraint condition, a virtual starting time constraint condition and an adjacent production line virtual starting time interval constraint condition.

The production line running state constraint condition is used for limiting the running state of the production line to be only a starting state or a non-starting state. Specifically, the constraint condition of the production line running state may include

Wherein p is _ik And vik, each production line can only be started or not started every day. The line has been activated indicating that the line has begun to plunge raw materials and begin to make the corresponding product from the raw materials.

The constraint condition for the starting state of the production line is used for limiting the production line to be in the starting state continuously after self-starting and cannot be changed into a state of not being startedA startup state. Specifically, the constraint condition of the production line starting state may include

It is understood that when p is _i0 If =1, it indicates that the i-th production line is started on day 0, that is, it indicates that the i-th production line is started on the first day in the prospect, and the day 0 does not have the previous day, therefore, the p _i(k-1) ≤p _ik K in this constraint may start with 1.

The production line earliest starting time constraint condition is used for constraining the calculation process of the variable value of the earliest starting time variable of the production line. Specifically, the constraint condition of earliest start time of the production line may include

The variable value of the planned earliest starting time variable of the ith production line is represented, namely the planned earliest starting time of the ith production line = the sum of the number of days that the ith production line is not started.

The production line starting time constraint condition is used for constraining the planned starting time of the production line not to be earlier than the production line starting time set by a user. Specifically, the constraint condition of the production line start-up time may include

The scheduled earliest starting time of the ith production line is later than the earliest starting time of the ith production line input by a user.

The virtual start time constraint condition is used for constraining the calculation process of the virtual start time of the production line.

Specifically, the virtual start-up time constraint may include

That is, the variable value of the virtual start-up time variable of the ith production line = the planned earliest start-up time variable d of the ith production line _i The sum of the variable value of (i) and the virtual delay time, i.e., = the variable value of the virtual start-up time variable of the ith production lineThe planned earliest starting time of the ith production line + the variable value of the non-started variable of the ith production line on the | K | day is multiplied by the linear body sequence increasing coefficient.

Wherein o is _i The value of (b) corresponds to the production line i. For example, when i =1, _Oi may be 1. For another example, when i =2, o _i May be 2.

It should be noted that, when the ith production line is started up in a day of the expectation period, the starting state of the production line continues to be the starting state, that is, v _i|K| And the virtual starting time of the ith production line is 0, and the virtual starting time of the ith production line is the planned earliest starting time of the ith production line. And when the starting time of the ith production line is after the expectation is finished, the v is _i|K| Is 1, therefore, the virtual start time of the i-th production line is not the planned earliest start time of the i-th production line.

In the embodiment of the application, through constructing the decision variable of the virtual starting time variable of the production line, the problem of calculation caused by the fact that the starting time of the production line input by a user is after the expectation is finished can be avoided, so that the abnormal condition of the production scheduling result is caused, meanwhile, the influence on the production line of the starting time of the production line in the expectation is avoided, and the reliability of the calculation of the production scheduling result can be improved.

The constraint condition of the virtual starting time interval of the adjacent production lines is used for limiting the interval days of the virtual starting time of the adjacent production lines to be not less than the minimum starting interval days between the adjacent production lines, so that the early wrong starting of the production lines is avoided.

Specifically, the adjacent production line virtual start-up time interval constraint condition may include

The interval time between the virtual starting time of the ith production line and the virtual starting time of the preposed production line of the ith production line is not less than the minimum starting interval days between the ith production line and the preposed production line of the ith production line.

For example, the production line capacity constraint conditions are used to constrain the capacity of the production line, the number of good products produced, and the number of good products delivered, and may include at least one of a capacity upper limit constraint condition, a capacity balance constraint condition, a planned capacity constraint condition, and a planned delivery quantity constraint condition.

The upper limit constraint condition is used to limit the actual upper limit of the capacity of the ith production line on the kth day to be the actual upper limit of the capacity corresponding to the actual start time of the ith production line on the kth day.

Specifically, the upper limit constraint of the capacity includes

It indicates that the actual upper capacity limit for the ith line on day k requires a backward shift in the earliest start-up time for the ith line.

For example, i =1, and the 1 st production line is the production line 1. The line 1 is started the second day in the prospect, i.e. at k = 1. When k =0, the signal is transmitted,

since the line 1 is not started on day 0, i.e. the first day in the prospect, V ₁₀ Is 1, and therefore,

that is, the upper limit of the actual capacity of the line 1 on day 0 is 0.

When k =1, the signal is transmitted,

wherein, V ₁₀ Is 1,V ₁₁ Is 0. Therefore, the temperature of the molten metal is controlled,

that is, the upper limit of the actual capacity of the production line 1 on the 1 st day is the upper limit of the capacity corresponding to the first day of the actual start-up of the production line 1.

The capacity balance constraint condition is used for constraining the planned input amount of raw materials in a day of a production line not to be larger than the input actual upper limit value of the capacity of the production line in the day, wherein the upper limit value of the capacity refers to the maximum number of products which can be produced by the capacity, and the products comprise good products and defective products. The planned input amount of raw materials is equivalent to the number of products which can be produced by the production line, and the products comprise good products and defective products.

Specifically, the capacity balance constraint may include

Illustratively, the planned yield constraint condition is used for constraining the number of planned good products in the production line not to be greater than the product of the number of products that can be produced in the production line and the yield, that is, the maximum number of good products that can be produced in the production line.

Specifically, the planned capacity constraint includes

k is less than the days of the production cycle alpha. Since the production line has no capacity in the production cycle, the product can be successfully obtained only after the production cycle, and therefore, when k is less than the number of days α in the production cycle, the planned capacity of the ith production line on the kth day is 0.

And, the planned capacity constraints can include

For example, i =1, and the 1 st production line is the production line 1. The expectation is 1 month No. 1 to 1 month No. 10, and the number of days of the production cycle α is 2. Line 1 started at month 1. Then the line 1 cannot get product, i.e. y, during the period from 1 month 1 to 2 ₁₀ And y ₁₁ Are all 0. At month No. 1, no. 3, i.e. k =2, the line gets the product, when s =0, v ₁₀ And =0. Y is ₁₂ ≤x ₁₀ ×w ₁₀ That is, the planned yield of the production line 1 in No. 1/3 is not greater than the product of the planned input amount of the raw materials of the production line 1 in No. 1/1 and the good product rate of No. 1/1, that is, not greater than the maximum number of good products that can be produced by the production line 1 in No. 1/1.

It can be seen that the yield variable is shifted backwards with the production cycle and the start-up time of the production line.

Similarly, the planned delivery quantity constraint condition is used for constraining the quantity of the planned delivery good products of the production line to be not greater than the product of the quantity of the production line and the passing rate, namely the quantity of the good products which can be delivered by the production line at most.

Specifically, the planned delivery quantity constraint includes

k is less than the days of production cycle alpha + the days of lead cycle beta. Since the production line is not delivered in the production cycle and the transportation cycle, that is, the good product of the production line is not received at the designated position, the product can be obtained only at the designated position after the production cycle and the transportation cycle, when k is less than the number of days of the production cycle α + the number of days of the delivery cycle β, the scheduled delivery number of the ith production line on the kth day is 0.

And, the planned capacity constraints can include

For example, i =1, and the 1 st production line is the production line 1. The prospect is 1 month No. 1 to 1 month No. 10, the production cycle days alpha is 2, and the transportation cycle is 3 days. Line 1 started at month 1. Then during the period from 1 month 1 to 5 months, the line 1 cannot deliver the product, i.e. the product produced by the line 1 cannot be received at the given position, at which time f _1k =0. At month 6, i.e. k =5, the line 1 can deliver the product successfully, and when s =0, v ₁₀ =0. F is a gas of ₁₅ ≤y ₁₂ ×r ₁₂ That is, the number of good products scheduled to be delivered by the production line 1 in No. 1/6 is not greater than the product of the number of good products scheduled to be delivered by the production line 1 in No. 1/3 and the pass rate of No. 1/3, that is, not greater than the maximum number of good products that can be delivered by the production line 1 in No. 1/3.

It can be seen that the throughput variable is intended to be offset backwards with the transport cycle and start-up time of the production line.

c. And setting a scheduling target.

Illustratively, the yield goal includes a forward rank goal and/or a reverse rank goal.

On one hand, when the user wants the production scheduling planning model to output the positive result, the user can set the positive target on the electronic device, that is, set the calculation rule of the positive target, which is actually a function.

Then, the electronic device responds to the input operation of the function of the positive displacement target of the user, and the function of the positive displacement target input by the user can be used as the target function of the positive displacement target in the scheduling planning model, so that the established scheduling planning model can select an optimal positive displacement scheme from the multiple determined positive displacement schemes based on the target function of the positive displacement target, and the scheduling planning model can determine the positive displacement target based on the optimal positive displacement scheme. Wherein the positive ranking scheme comprises variable values of the decision variables.

In some embodiments, the objective function of the positive row target may be max Σ _k∈K ∑ _i∈I f _ik I.e., the maximum of the sum of the total number of scheduled deliveries that all production lines expect to correspond to, i.e., the maximum total number of deliveries. Due to f _ik Instead of a fixed value, a set of values, i.e. a plurality of values, is assigned to, thus, Σ _k∈K ∑ _i∈I f _ik Also corresponding to a set of values. Accordingly, the objective function of the positive rank result is used to derive the sigma _k∈K ∑ _i∈I f _ik And selecting the maximum value from the corresponding value set, and taking the maximum value as a positive row result.

It should be understood that f is due to _ik The determination is related to other decision variables, and if the variable values of other decision variables are different, different f may be obtained _ik And therefore, different positive-ranking schemes exist. The optimal positive arrangement scheme is that _k∈K ∑ _i∈ _I f _ik The value of (b) is the largest, the value of the variable of the other decision variable.

On the other hand, when the user wants the scheduling planning model to output the inverted result, the user may set the inverted target in the electronic device, that is, set the calculation rule of the inverted target, which is actually a function.

Then, the electronic device responds to the input operation of the function of the inverted target of the user, and the function of the inverted target input by the user can be used as the target function of the inverted target in the scheduling planning model, so that the established scheduling planning model can select an optimal inverted scheme from the multiple determined inverted schemes based on the target function of the inverted target, and the scheduling planning model can determine the inverted target based on the optimal inverted scheme. Wherein the inversion scheme comprises variable values of the decision variables.

Wherein, the inverted target indicates the configuration of the production line resource. For example, the inverted target may include one or more of the latest start time of the earliest production line, the latest start time of all production lines, the minimum number of start production lines, the latest start time of the earliest production line, and the minimum number of start production lines.

Accordingly, the latest start time of the earliest production line represents the latest start time of the first production line on the basis of the total production capacity. The target function of the latest starting time of the earliest production line is maxd ₀ Since the 0 th production line is the earliest started production line, it is determined that the planned earliest start time of the 0 th production line may be a time range based on the scheduling constraint conditions, and the objective function of the latest start time of the earliest production line is used to select the maximum value from the time range, and the maximum value is used as the inverted target of the latest start time of the earliest production line.

The latest starting time of all the production lines represents the sum of the planned earliest starting time of all the production lines when each production line is started as late as possible on the basis of finishing the target total production performance. The objective function of the latest starting time of all the production lines can be max sigma _i∈I d _i . Since the scheduled earliest startup time of the 0 th production line is determined to be a time range, i.e., d _i Possibly for a time frame. Correspondingly, d for all production lines _i The sum is also a value range, and the target function of the latest starting time of all production linesThe method is used for selecting the maximum value from the value range and taking the maximum value as the latest starting time of all the production lines.

The minimum number of activated lines represents the minimum number of lines that the supplier needs to activate based on being able to complete the target total production capacity. The objective function for the minimum number of production lines can be min Σ _i∈I p _i(|K|-1) 。

The production line can be determined to be in the starting state continuously after being started automatically based on the scheduling constraint conditions, and therefore the number of the production lines in the starting state in the last day in the prospect period can be used as the number of the starting production lines. As each line may or may not be started. Because each production line can be started or not, the number of the started production lines is a set, the objective function with the minimum number of the started production lines is used for determining the set, and the minimum value is determined from the set and is the minimum number of the started production lines.

The latest starting time and the minimum number of the starting production lines of the earliest production line represent the minimum number of the production lines required to be started by a supplier while the earliest production line is started as late as possible on the basis that the total target production capacity can be completed. The objective function of the earliest production line latest starting time and the least number of the starting production lines can be max (M × d) ₀ -∑ _i∈I p _i(|K|-1) ). Wherein, M is a preset coefficient, and the value of M is a positive number which is large enough. For example, there are three inversion schemes, the first inversion scheme is d ₀ (= 5) and ∑ _i∈I p _i(|K|-1) A value of 10 indicates that the total number of lines required by the supplier to start up on day 5 when line 0 starts up is 10, the M x d 0-sigma _i∈I p _i(|K|-1) The value of (b) is A.

Second inverted arrangement, d ₀ (= 5) and ∑ _i∈I p _i(|K|-1) At 11, it means that the total number of lines required to be started by the supplier is 11 when the first line is started on day 5, and this M × d ₀ -∑ _i∈I p _i(|K|-1) The value of (B) is B.

The third inversion scheme is d ₀ =3 and ∑ _i∈I p _i(|K|-1) Is 8, indicated in0 lines started on day 3, the total number of lines required by the supplier to start up was 5, this M x d ₀ -∑ _i∈I p _i(|K|-1) The value of (D) is C.

When A > B and A > C as described above, the first inversion scheme is optimal, i.e., the latest start time of the earliest production line is day 5, i.e., the sixth day in the prospect, and 11 production lines are started.

As shown in fig. 5, when a relevant person constructs an input variable and a decision variable on an electronic device (such as in the integer programming model on the electronic device), and sets a scheduling constraint condition and a scheduling target, that is, after the electronic device obtains the input variable, the decision variable, the constraint condition and the scheduling target of the scheduling programming model set by a user, the electronic device calls a relevant interface (such as a modeling interface) of an integer programming solver to perform coding based on the input variable, the decision variable, the constraint condition and the scheduling target, so as to obtain a corresponding scheduling model, that is, a programming solver. The encoding process can be understood as a process of compiling the scheduling planning model to obtain a corresponding application. The planning solver is used for outputting a scheduling result, and the scheduling result comprises a scheduling target and/or a scheduling scheme.

Wherein, the scheduling scheme indicates the planned input and output conditions of raw materials of each production line. The scheduling scheme is determined based on the variable value of the decision variable corresponding to the scheduling target.

In some embodiments, the schedule may be represented by a schedule table such as that shown in table 1. The scheduling table comprises the daily input, output and delivery conditions of raw materials of each production line in the prospect period.

TABLE 1

In other embodiments, for a scenario where the start-up time of the production line is after the end of the prospect, the production scheduling scheme may be represented by a production scheduling table as shown in table 2. Wherein, the virtual (dummy) date in the scheduling table indicates the starting state of the production line after the expectation is finished.

TABLE 2

Of course, the scheduling scheme may be represented by a graph as shown in FIG. 1.

In the embodiment of the application, the fact that the capacity upper limit value of the production line and the yield of the production line are improved along with the production process is considered, and when the scheduling planning model is created, corresponding input variables, decision variables, scheduling constraint conditions and the like are set, so that the scheduling result determined by the scheduling planning model is more consistent with the actual production situation. In the modeling process, the climbing curve is supported to be aligned with the actual starting time of the production line, so that the scheduling result is more objective and reliable. And the scheduling planning model automatically adjusts the use number and the starting time of the production line, so that the production line resource configuration with the lowest cost can be output according to the target total energy requirement, and the scheduling is not required to be performed based on the fixed production line configuration.

In the embodiment of the present application, the essence of inverted and forward rows refers to that under a condition of a constraint (for example, the number of production lines, the start date of each production line, etc.), a decision is made on key business elements (for example, planned input and output of raw materials of each production line, etc.), and an optimal production scheduling scheme is obtained, so as to obtain the maximized capacity, or the configuration of production line resources with the lowest cost and risk. Therefore, in order to determine the scheduling result, the electronic device creates a scheduling model by using the integer programming model and the input variables, the decision variables, the scheduling constraints and the scheduling targets set by the user. The scheduling planning model can determine variable values of input variables based on relevant information input by a user, select proper scheduling constraint conditions to carry out solving calculation to obtain scheduling results, realize accurate and rapid calculation of the scheduling results, improve the determination efficiency of the scheduling results and the reliability of the scheduling results, and ensure the quality of scheduling schemes in the scheduling results.

The scheduling planning model has universality and can be used for determining scheduling plans of various products to be listed, namely products to be scheduled, so that instant volume production of the products is realized. And the scheduling constraint conditions in the scheduling planning model are decoupled, so that relevant personnel can set the scheduling constraint conditions in the scheduling planning model according to actual use requirements, and the scheduling planning model can select proper scheduling constraint conditions to constrain decision variables when determining scheduling results, so that the scheduling planning model can be suitable for calculation scenes of different scheduling results, namely different calculation scenes can correspond to one set of codes, and the maintainability is high, thereby effectively reducing the maintenance cost.

Example two

The embodiment of the application provides a production scheduling method. In this embodiment, after the setup planning model is created, the electronic device may output a corresponding setup result by using the setup planning model according to the setup requirement of the user, so as to achieve fast acquisition of the setup result, and the setup constraint condition in the setup planning model takes into account the actual production condition of the product, so that the setup result determined based on the setup constraint condition is more objective and reliable. Specifically, as shown in fig. 6, the picture display method provided in the embodiment of the present application may include S101 to S103.

S101, the electronic equipment acquires product production information corresponding to products to be scheduled, wherein the product production information comprises one or more of a climbing curve, production line adding limit information, product time information, target total energy and material supply information of each production line.

Illustratively, the product production information is used to determine variable values for input variables of the scheduling planning model. The product line in the product production information indicates a product line available for manufacturing the product, i.e., available supplier product line resources.

The climbing curve includes at least one of a productivity climbing curve, a yield climbing curve and a throughput climbing curve.

The productivity climbing curve indicates the corresponding relation between the time after the production line is started and the productivity. Such as how many products the line 1 can generate on the first day after start-up, how many products the line 1 can generate on the second day after start-up, and so on.

The yield climbing curve indicates the corresponding relation between the time after the production line is started and the probability of good products in the products manufactured by the production line. If the number of target products that can be produced by the production line 1 on the first day after the start-up is 100, and 90 of the 100 products are good products, the good product rate on the first day after the start-up is 90%.

The passing rate climbing curve indicates the corresponding relation between the time and the passing rate of the product in the transportation process. In short, the product is lost during transport, and the pass rate indicates the proportion of the product that is not lost to all of the product transported. For example, if 2 good products are lost on the first day of 100 good products produced by the transportation line 1, the passing rate on the first day in the transportation process is 98%.

The total target capacity represents the number of good products that the supplier can deliver in the end. The product is actually good.

It should be understood that when the scheduling result of the target product required by the user is a positive scheduling result, the product production information may not include the total target performance, which is a positive scheduling goal that the scheduling planning model needs to solve.

The production line adding limit information includes the earliest starting time of each production line and the starting time difference between the production lines.

The above product time information includes at least one of a prospect information, a production period and a transportation period.

The production cycle refers to the total time from the start of production to the end of production, and is also referred to as the product manufacturing period.

The transportation cycle refers to the total time from output to delivery of the product, wherein the delivery refers to the transportation of the product to a specified location (such as a specified warehouse).

The prospect is also called a plan prospect and indicates the time range covered by the production plan. The prospect information may include a start date to an end date of the prospect. For example, the expected start time is No. 1, the end time is No. 30, and the forward target indicates how much maximum capacity can be achieved in the time range from No. 1 to No. 30 of 12 months.

The above-mentioned material supply information indicates the supply of each raw material for producing a product, that is, the number of each raw material that can be charged each day in the expectation period.

In some embodiments, the product production information may be input by a user on an associated interface displayed by the electronic device. That is, the related interface has related control (such as text box) so that the user can input the corresponding product production information by using the related control. The product production information may also be read by the electronic device from a file uploaded by the user. Of course, the input mode of the product production information may be other modes, and a description thereof is omitted here.

And S102, the electronic equipment determines variable values of input variables of the scheduling planning model according to the product production information.

In this embodiment, after obtaining the product production information input by the user, as shown in fig. 4, the electronic device may perform scene abstraction to determine variable values of input variables of the production scheduling model from the product production information.

For example, the input variables of the scheduling planning model include a production line number set I. The electronic device may be a production line to be scheduled, which is determined based on production line adding limit information or a climbing curve of each production line, that is, all production lines that can be used in production. Then, the electronic device may assign a number to each production line, where the numbers of the production lines are different.

In some embodiments, the electronic device may first determine the order of arrangement between the production lines. Then, the electronic device may assign a serial number to each production line in sequence according to the arrangement order among the production lines. For example, the line number is an increasing number starting from 0. For convenience of description, the present application will take the increasing numbers with the line number starting from 0 as an example to introduce relevant contents. The line number may also be other types of numbers, such as a number that starts to increment, or a number that decrements, etc.

For example, the arrangement order between the production lines may be the arrangement order of the earliest start-up time of the production lines. That is, the electronic device ranks the production lines based on the order of the earliest starting time of the production lines, and the earlier the earliest starting time of the production lines is, the higher the ranking of the production lines, that is, the ranking order is. For example, the earliest start time of the production line a is the earliest, and the ranking of the production line a may be 0, that is, the number of the production line a may be 0. Of course, the arrangement order between the production lines may be determined based on other manners, for example, based on the limited period of the production lines.

The arrangement sequence among the production lines represents the starting time relationship between each production line and the production lines before and after the production line, namely the starting interval time. The electronic equipment can express the arrangement sequence between the production lines through the tree structure, each production line is a node, the edge weight between adjacent nodes expresses the number of the starting minimum interval days between adjacent production lines corresponding to the adjacent nodes, and therefore the electronic equipment can quickly determine the adjacent production line condition of each production line based on the tree structure corresponding to the production line. As shown in fig. 7, the front line of the line b is the line a, and the minimum number of days between the line a and the line b is 2 days.

As another example, the input variables may include the number of days of the production cycle α. The electronic device may use the production cycle in the product production information as a variable value of the number of days α of the production cycle.

As another example, the input variable may include the number of lead cycle days β. The electronic device may use the transportation period in the product production information as a variable value of the number of days of the lead period.

For another example, the input variables may include a cumulative input variable s of the j-th material on the k-th day _jk . The electronic equipment can read the daily input amount of each material in the expectation period from the material supply information in the product production information, so that the daily accumulated input amount of each material in the expectation period can be determined. For example, the cumulative amount of the raw material 1 charged on day 1 is the sum of the supply amount of the raw material 1 on day 0 and the supply amount of the raw material 1 on day 1.

For another example, the input variables may include an earliest startup time variable e of the ith production line _i . The electronic device may determine the earliest start time of each production line from the production line adding limit information in the product production information.

As another example, the input variables may include a pre-production line variable π for the ith production line _i . After determining the order of the products, the electronic device may determine the serial number of the pre-production line of the ith production line, that is, the pre-production line variable pi of the ith production line, according to the tree structure of the production line _i The value of (d) is determined.

For another example, the input variables may include an upper capacity limit variable of the ith production line on the kth day. The electronic device can be determined from the productivity climbing curve in the product production information. For example, k =1,i =1, the electronic device can read the upper limit of the capacity on the 1 st day from the capacity ramp curve of the production line 1, so as to obtain the upper limit of the capacity on the 1 st day of the production line 1.

For another example, the input variables may include yield variable of the ith production line on the kth day. The electronic device can be determined from a yield climbing curve in the product production information.

For another example, the input variables may include a throughput rate variable r of the ith production line on the kth day _ik . The electronic device may be determined from a throughput ramp curve in the product production information.

Similarly, the electronic device may determine the variable values of other input variables based on the product production information, and a detailed description thereof is omitted here.

And S103, the electronic equipment takes the variable value of the input variable as input, and operates the scheduling planning model to output a scheduling result. The scheduling planning model is used for performing constraint calculation on parameter values of decision variables by using scheduling constraint conditions in the scheduling planning model and variable values of the input variables to determine scheduling results.

Wherein the scheduling result may comprise a positive or negative scheduling result. The scheduling result may include a scheduling objective and/or a scheduling plan. Accordingly, the scheduling objective includes a forward or reverse target. The scheduling scheme may include a forward scheduling scheme or an inverted scheduling scheme.

In some embodiments, the scheduling result is selected by the user, so that the scheduling planning model can output the scheduling result required by the user. Correspondingly, the input variables may also include a result output variable, and the variable value of the result output variable indicates the type of the scheduling result that needs to be output by the scheduling planning model, that is, the forward scheduling result and/or the backward scheduling result needs to be output.

Specifically, the electronic device receives a selection operation of a user on a scheduling result option in the first interface, and in response to the selection operation, the electronic device determines a target result identifier, and uses the target result identifier as an input of the scheduling plan, so that the scheduling plan model finally outputs a scheduling result corresponding to the target result identifier. For example, the user selects a positive result option, the electronic device determines that the target result identifier is a positive result identifier (such as 1 or other characters) in response to the selection operation of the positive result option, and the electronic device inputs the positive result identifier to the production planning model as a variable value of an output result variable of the production planning. The scheduling planning model selects scheduling constraint conditions corresponding to the forward-ranking target, performs constraint calculation on variable values of decision variables corresponding to the forward-ranking target based on the scheduling constraint conditions corresponding to the forward-ranking target and the variable values of the input variables, and finally outputs a forward-ranking result.

For another example, the user selects the inverted result option, the electronic device determines that the target result identifier is an inverted result identifier (such as 0 or other characters) in response to the selection operation of the inverted result option, the electronic device inputs the inverted result identifier as a variable value of an output result variable of the scheduling plan to the scheduling plan model, the scheduling plan model selects a scheduling constraint condition corresponding to the inverted result, and performs constraint calculation on a variable value of a decision variable corresponding to the inverted result based on the scheduling constraint condition corresponding to the inverted target and the variable value of the input variable, so as to finally output the inverted result. The scheduling planning model can flexibly select related information such as scheduling constraint conditions and the like according to user requirements so as to realize flexible switching generation of scheduling results, and therefore the electronic equipment can flexibly output the scheduling results according to the user requirements. The inverted result comprises an inverted target and/or an inverted scheme corresponding to the inverted target, and the inverted target can comprise one or more of the latest starting time of the earliest production line, the latest starting time of all production lines, the minimum number of the started production lines, the latest starting time of the earliest production line and the minimum number of the started production lines.

Illustratively, as shown in fig. 8, the first interface includes the positive result option 10 and the negative result option 11. The user's selection of the positive result option 10 is the selection of the positive result option. Alternatively, the operation of the user selecting the inverted result option 11 is the selection operation of the inverted result option.

It should be understood that the content displayed in the first interface and the positive result option 10 and the negative result option 11 are only an example, and the first interface may also include other content, and the positive result option 10 and the negative result option 11 may also be represented in other forms (such as a list), which is not limited herein. In addition, the input variables in the scheduling planning model may not include result output variables, and the result output variables may be input independently from the input variables.

In this embodiment, the user can select the type of inverted result to be output, that is, select the inversion target. Specifically, the electronic device receives a selection operation of a user on a first inverted target option in a second interface, and in response to the selection operation, the electronic device uses an identifier of the first inverted target option as an input of the scheduling planning model, so that the scheduling planning model selects a scheduling constraint condition corresponding to the first inverted target, performs constraint calculation on a variable value of a decision variable corresponding to the first inverted target by using the scheduling constraint condition and a variable value of an input variable, and finally outputs an inverted result including the first inverted target. The inverted result can also comprise an inverted scheme corresponding to the first inverted target.

Illustratively, as shown in fig. 9, the second interface includes four options, i.e., the latest starting time of the earliest production line, the latest starting time of all production lines, the minimum number of the started production lines, the latest starting time of the earliest production line, and the minimum number of the started production lines. And when the latest starting time of the earliest production line selected by the user is the first inverted target option, the latest starting time of the earliest production line is the first inverted target option.

In some embodiments, the user may select the inverted result option after selecting the inverted result option, and after selecting the inverted result option, the user may continue to select the inverted target required to be included in the inverted result, so that the scheduling model can output the scheduling result required by the user. Correspondingly, the input variables may further include a drainage target output variable, and the variable value of the drainage target output variable indicates the type of the drainage target that the production planning model needs to output, that is, the output drainage target may include one or more of the latest start time of the earliest production line, the latest start time of all production lines, the minimum number of started production lines, the latest start time of the earliest production line, and the minimum number of started production lines.

Specifically, the electronic device receives a selection operation of a user on a first inverted target option in a second interface, and in response to the selection operation, the electronic device determines an inverted target output identifier (i.e., a variable value of an inverted target output variable), and uses the inverted target output identifier as an input of the scheduling plan, so that the scheduling plan model finally outputs an inverted result corresponding to the inverted target output identifier, that is, the inverted result may include the first inverted target and/or an inverted scheme corresponding to the first inverted target. .

In other embodiments, the scheduling planning model corresponds to the scheduling result, and the user does not need to select the scheduling result required to be output by the scheduling planning model, so that the scheduling result is output quickly, but the output scheduling result may not be required by the user. For example, the scheduling planning model corresponds to the positive scheduling result, that is, after obtaining the variable value of the input variable, the scheduling planning model directly performs the related calculation to obtain and output the corresponding positive scheduling result.

For another example, the scheduling planning model corresponds to the inverted result, that is, the scheduling planning model can be used to output the inverted result, that is, after obtaining the variable value of the input variable, the scheduling planning model directly performs the relevant calculation to obtain and output the corresponding inverted result, and in short, the scheduling planning model can output the corresponding scheduling result without the user selecting the inverted result.

It should be noted that the inverted result is determined based on the set target capacity, and the positive result requires the capacity corresponding to the result, so that the user does not use the scheduling model to determine the inverted result and the positive result at the same time, that is, the scheduling model generally only outputs the inverted result or the positive result.

In some embodiments, for a production line, the unified standardization of production and output per day after startup of the production line may be 3 stages, the 3 stages being planned input, planned output, and planned delivery, respectively.

The planned input refers to the quantity of raw materials planned to be input by the production line so as to produce corresponding products.

The planned output refers to the number of products planned to be produced by the production line each day after the production line is started, i.e., the number of products planned to be produced by the production line each day in the production cycle. The product herein may be referred to as a good product.

Scheduled delivery refers to the number of products that the production line can deliver per day after passing through the scheduled output phase. The product herein may be referred to as a good product.

There are corresponding decision variables for these three phases. If the decision variable corresponding to the planned input stage is the planned input variable x of the raw material of the ith production line on the k day _ik The decision variable corresponding to the planned output stage is the planned delivery quantity variable f of the ith production line on the k day _ik The decision variable corresponding to the planned delivery stage is the planned output yield variable l of the ith production line on the kth day _ik . The decision variables corresponding to the three phases are the objects to be solved by the electronic equipment.

In the production process of the product, the corresponding amount of raw materials is deducted from each product put into production on the same day, and therefore, relevant constraint conditions (such as the material balance constraint conditions and the like) are set.

Since the input quantity of raw materials per day of the production line is limited by the upper limit value of the production capacity of the production line on the day, the production capacity of the production line is in a climbing state, and the production capacity of the production line on the first day needs to be aligned with the production line on the first day after the production line is started, relevant constraint conditions (such as the production line input constraint condition, the production line production capacity constraint condition and the like) are set.

Similarly, the daily capacity (referred to herein as the non-defective capacity) of the production line is limited by the yield of the production line on the day, and the yield is also in a climbing state (e.g., 1% per day), and the capacity of the production line on the first day needs to be aligned with the capacity of the production line on the first day after the production line is started, so that relevant constraint conditions (such as the production line feeding constraint condition, the production line capacity constraint condition, and the like) are set, so that the production scheduling result output by the production scheduling planning model with the relevant constraint conditions, such as the variable values of the decision variables corresponding to the three stages, better conforms to the actual production condition, and the reliability of the production scheduling result is ensured.

In some embodiments, in the actual production, the related personnel may set an earliest starting time for each production line in advance, that is, the user may input the earliest starting time of the production lines and the starting time difference between the production lines. Thus, as shown in FIG. 10, the constraint of each line with the earliest startup time, and the line need to meet both the absolute startup time constraint, which is the expectation, and the relative startup time, which is the difference in startup time between lines. Therefore, related constraint conditions (such as the production line feeding constraint conditions and the like) are set in the integer programming model by related personnel, so that the condition that the starting time of the production line is wrong can be avoided for the scheduling result solved by the created scheduling programming model, and the accuracy of the scheduling result is further ensured.

In some embodiments, the user may also adjust the scheduling constraints in the scheduling planning model according to the scenario requirements. For example, when the user wants to determine the scheduling result of the mobile phone, the scheduling constraint condition in the scheduling planning model on the electronic device may be adjusted by the electronic device according to the condition of the provider production line of the mobile phone, and for example, when the user wants to determine the scheduling result of the clothes, the scheduling constraint condition in the scheduling planning model on the electronic device may be adjusted by the electronic device according to the condition of the provider production line of the clothes.

The adjustment of the scheduling constraint condition may be to delete, add or modify the scheduling constraint condition.

For example, the adjustment process of the scheduling constraint may include:

when a user wants to modify the scheduling constraints in the scheduling planning model, a modification operation is input on the electronic equipment, and the modification operation is used for triggering the electronic equipment to modify the first scheduling constraints in the scheduling planning model.

The electronic device modifies the first scheduling constraint in the scheduling planning model in response to the modifying operation.

When the user wants to delete the scheduling constraint condition in the scheduling planning model, a deleting operation is input on the electronic equipment, and the modifying operation is used for triggering the electronic equipment to delete the second scheduling constraint condition in the scheduling planning model.

The electronic device deletes the second scheduling constraint in the scheduling planning model in response to the modify operation.

When a user wants to add a scheduling constraint condition in the scheduling model, an adding operation is input on the electronic equipment, and the adding operation is used for triggering the electronic equipment to add a first cozy scheduling constraint condition in the scheduling model.

The electronic device adds the third constraint in the scheduling planning model in response to the adding operation.

Due to the decoupling between the scheduling constraints in the scheduling planning model, the application supports the adjustment of the scheduling constraints in the scheduling planning model. The user can input relevant adjustment operations (such as modification, addition, deletion and the like) of the scheduling constraint conditions on the electronic equipment according to the scene requirements of the product, and the electronic equipment responds to the adjustment operations to correspondingly adjust the scheduling constraint conditions in the scheduling planning model, so that the scheduling planning model can output corresponding scheduling results according to the specific scene requirements, and the maintainability of the scheduling planning model is improved.

In the embodiment of the application, the electronic device utilizes the scheduling planning model to solve the corresponding scheduling result, and the scheduling constraint condition in the scheduling planning model conforms to the actual production condition, so that the reliability of the scheduling result output by the scheduling planning model is higher, and the scheduling result conforms to the actual production condition, thereby avoiding that the determined forward-ranking target is larger or smaller, and further avoiding the problem of radical excitation in the S & OP formulation or the problem of loss of the product order. And the sufficient research and development progress can be ensured, the product quality is reliable, and the contract signing cost of a supplier can be saved.

It should be noted that the quantities related to the raw materials are actually quantities related to various raw materials, for example, the raw material input quantity refers to the quantity required to input each raw material, the quantity required to input each raw material is the same, and the quantity is actually a set quantity. For example, 3 cameras and 1 display screen are needed to produce a mobile phone, and 3 cameras are used as a set of cameras. When the input quantity of the raw materials is 100, 100 sets of cameras and 100 sets of display screens are required to be input.

The above describes a case where the equipment for creating the scheduling planning model and the equipment for determining the scheduling result by applying the scheduling planning model are the same equipment, and of course, there is a case where the equipment for creating the scheduling planning model and the equipment for determining the scheduling result by applying the scheduling planning model are not the same equipment. For example, the relevant personnel creates a scheduling model on a first device (i.e., the application of the above-mentioned planning solver), and a second device installed with the scheduling model can determine a scheduling result by using the scheduling model. The process of determining the scheduling result by the second device applying the scheduling planning model is similar to the process of determining the scheduling result by the electronic device applying the scheduling planning model, and the process of creating the scheduling planning model by the first device is similar to the process of creating the scheduling planning model by the electronic device, and is not repeated here.

In some embodiments, when determining the scheduling result, the electronic device may also determine the scheduling result without using the scheduling planning model, but directly calculate using the input variable, the decision variable, and the scheduling constraint condition to determine the corresponding scheduling result. The process of determining the scheduling result by the electronic device using the input variable, the decision-making variable and the scheduling constraint condition is similar to the process of determining the scheduling result by the electronic device using the scheduling planning model, for example, the electronic device determines a variable value of the input variable according to the product production information, and then performs constraint calculation on a parameter value of the decision-making variable by using the scheduling constraint condition and the variable value of the input variable to determine the scheduling result. The input variable, the decision variable and the scheduling constraint condition are input and set on the electronic equipment in advance by a user.

In some embodiments, the present application provides a computer readable storage medium comprising computer instructions which, when run on an electronic device, cause the electronic device to perform the method as described above.

In some embodiments, the present application provides a computer program product which, when run on an electronic device, causes the electronic device to perform the method as described above.

Through the description of the above embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical functional division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another device, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or multiple physical units, that is, may be located in one place, or may be distributed in multiple different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.

The above description is only an embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed in the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of scheduling production, the method comprising:

the method comprises the steps that electronic equipment obtains product production information corresponding to a product to be scheduled, wherein the product production information comprises one or more of a climbing curve of at least one production line, production line adding limit information, product time information, target total electrical energy and material supply information; the climbing curve of the at least one production line comprises at least one of a productivity climbing curve, a yield climbing curve and a passing rate climbing curve of each production line in the at least one production line; the production line adding limiting information comprises the earliest starting time of each production line and/or the starting time difference between the production lines in at least one production line; the product time information comprises at least one of a production cycle, a prospect and a transportation cycle of the product to be scheduled; the material supply information indicates a supply quantity of at least one raw material at the prospective;

the electronic equipment determines the variable value of a preset input variable according to the product production information;

the electronic equipment performs constraint calculation on a preset decision variable based on a preset scheduling constraint condition and the variable value of the input variable to obtain a scheduling result, wherein the scheduling result comprises a positive scheduling result or a reverse scheduling result; the preset decision variable indicates a service element to be determined, and the service element indicates at least one of the capacity, the feeding quantity, the starting time, the yield and the passing rate of the production line; and the preset scheduling constraint condition is used for constraining the value of the preset decision variable based on the variable value of the input variable.

2. The method of claim 1, wherein the preset input variables are input variables in a scheduling planning model; the preset decision variables are decision variables in the scheduling planning model, and the preset scheduling constraint conditions are scheduling constraint conditions in the scheduling planning model;

the electronic equipment carries out constraint calculation on a preset decision variable based on a preset scheduling constraint condition and the variable value of the input variable to obtain a scheduling result, and the method comprises the following steps:

the electronic equipment takes the variable value of the preset input variable as input, and operates the scheduling planning model to output the scheduling result of the product to be scheduled; the scheduling planning model is used for performing constraint calculation on the preset decision variables by using the preset scheduling constraint conditions and the variable values of the preset input variables to obtain scheduling results.

3. The method of claim 1 or 2, wherein the product production information includes an earliest start time of each production line, and the preset input variable includes a pre-production line variable of a production line;

the electronic equipment determines the variable value of a preset input variable according to the product production information, and the method comprises the following steps:

the electronic equipment sorts the production lines based on the earliest starting time of the production lines to obtain the arrangement sequence of the production lines;

for each production line, the electronic equipment determines the serial number of the front production line of the production line from the arrangement sequence of the production lines, and takes the serial number of the front production line of the production line as the variable value of the front production line variable of the production line.

4. The method of claim 1 or 2, wherein the product production information comprises an earliest startup time of a production line, and the preset input variable comprises a pre-production line variable of the production line;

for each node in the tree structure chart, the electronic equipment acquires the number of a production line indicated by the previous node of the node, and takes the number of the production line indicated by the previous node as the variable value of a preset production line variable of the production line indicated by the node.

5. The method according to claim 4, wherein the weight of the connecting edge between adjacent nodes in the tree structure diagram is the starting time difference between the adjacent nodes.

6. The method of any one of claims 1 to 5, wherein the preset scheduling constraints comprise one or more of numerical constraints, material balance constraints, inverted ramp constraints, production line charging constraints, and production line capacity constraints;

the numerical constraint condition is used for constraining the value range of a preset decision variable; the material balance constraint condition is used for constraining the total usage amount of the raw materials not to be larger than the accumulated input amount of the raw materials; the inverted climbing constraint condition is used for constraining the total quantity of products delivered by a production line to be not less than the total target capacity; the production line feeding constraint condition is used for constraining the starting time of the production line;

and the production line capacity constraint condition is used for constraining the capacity of the production line and/or the quantity of delivered good products.

7. The method of claim 2, wherein the operating the scheduling planning model to output the scheduling results for the product to be scheduled comprises:

the electronic equipment receives selection operation of a user on a target scheduling result option in a first interface; wherein the target scheduling result option indicates a positive scheduling result or a negative scheduling result;

and the electronic equipment responds to the selection operation of the target scheduling result option, takes the target scheduling result option as input, and operates the scheduling planning model to output a scheduling result corresponding to the target scheduling result option.

8. The method of claim 2, wherein the inverted result comprises an inverted target, the inverted target comprising one or more of a latest start time of an earliest production line, a latest start time of all production lines, a minimum number of started production lines, a latest start time of an earliest production line, and a minimum number of started production lines;

the operation of the scheduling planning model outputs the scheduling result of the product to be scheduled, which comprises the following steps:

the electronic equipment receives the selection operation of a user on a first inverted target option in a second interface; the first inverted target option indicates one or more of the latest starting time of the earliest production line, the latest starting time of all production lines, the minimum number of the started production lines, the latest starting time of the earliest production line and the minimum number of the started production lines;

and the electronic equipment responds to the selection operation of the first reverse arrangement target option, takes the first reverse arrangement target option as an input, runs the scheduling planning model and outputs a reverse arrangement result corresponding to the first reverse arrangement target option, wherein the reverse arrangement result comprises a reverse arrangement target corresponding to the first reverse arrangement target option.

9. The method according to any one of claims 1 to 8, wherein the preset decision variables comprise at least one of a planned input amount of raw materials for the ith production line on the k th day, a planned capacity variable for the ith production line on the k th day, a planned delivery amount variable for the ith production line on the k th day, an actual capacity upper limit variable for the ith production line on the k th day, a start-up variable for the ith production line on the k th day, a non-start-up variable for the ith production line on the k th day, a planned earliest start-up time variable for the ith production line, a virtual start-up time variable for the ith production line, a planned yield variable for the ith production line on the k th day, and an accumulated consumption variable for the jth raw material on the k th day, wherein i, k, j are non-negative integers, the ith production line is any one of the at least one production line, the kth day is any one of the at least one raw material.

10. An electronic device, wherein the electronic device is a first electronic device, the electronic device comprising a display screen, a memory, and one or more processors; the display screen, the memory and the processor are coupled; the display screen is for displaying images generated by the processor, the memory is for storing computer program code, the computer program code comprising computer instructions; the computer instructions, when executed by the processor, cause the electronic device to perform the method of any of claims 1-9.

11. A computer readable storage medium comprising computer instructions which, when run on an electronic device, cause the electronic device to perform the method of any of claims 1-9.