CN116703262B - Distribution resource adjustment method, distribution resource adjustment device, electronic equipment and computer readable medium - Google Patents
Distribution resource adjustment method, distribution resource adjustment device, electronic equipment and computer readable medium Download PDFInfo
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Abstract
Embodiments of the present disclosure disclose a distribution resource adjustment method, apparatus, electronic device, and computer-readable medium. One embodiment of the method comprises the following steps: acquiring an order information set of the power equipment, which is distributed by a power equipment supply end in a preset time period; generating a power equipment order prediction information set based on the power equipment order information set; determining a distribution upper limit value corresponding to the power equipment supply end; determining the quantity of the power equipment order prediction information included in the power equipment order prediction information set as an order prediction information quantity; generating supply end distribution detection information according to the distribution quantity upper limit value and the order forecast information quantity; and adjusting the distribution resources of the power equipment supply end according to the supply end distribution detection information. The implementation mode can adjust the distribution resources in advance, and reduces the waste of transportation resources.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a method, an apparatus, an electronic device, and a computer readable medium for adjusting distribution resources.
Background
In the process of transporting the power equipment, the delivery delay is often caused by insufficient delivery resources of the supply end. Currently, in order to avoid delivery delay, the following methods are generally adopted: the transport vehicles are directly added to avoid delivery delays.
However, the following technical problems generally exist when the above-described manner is adopted:
firstly, directly adding transport vehicles, and when the number of orders of the power equipment is small, easily causing the waste of transport resources;
second, the relationship between the delivery distance of the supply end and the delivery address of the order is not considered, so that the supply end cannot deliver in time, and delivery delay is caused.
The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.
Disclosure of Invention
The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose a distribution resource adjustment method, apparatus, electronic device, and computer readable medium to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a method for adjusting a distribution resource, the method comprising: acquiring an order information set of the power equipment, which is distributed by a power equipment supply end in a preset time period; generating a power equipment order prediction information set based on the power equipment order information set, wherein the power equipment order information in the power equipment order information set corresponds to the power equipment order prediction information in the power equipment order prediction information set; determining a distribution upper limit value corresponding to the power equipment supply end; determining the quantity of the power equipment order prediction information included in the power equipment order prediction information set as an order prediction information quantity; generating supply end distribution detection information according to the distribution quantity upper limit value and the order forecast information quantity; and adjusting the distribution resources of the power equipment supply end according to the supply end distribution detection information.
In a second aspect, some embodiments of the present disclosure provide a dispensing resource adjustment device, the device comprising: an acquisition unit configured to acquire a power equipment order information set distributed by a power equipment supply end within a preset time period; a first generation unit configured to generate a power equipment order prediction information set based on the power equipment order information set, wherein power equipment order information in the power equipment order information set corresponds to power equipment order prediction information in the power equipment order prediction information set; a first determination unit configured to determine an upper limit value of a delivery amount corresponding to the power equipment supply terminal; a second determination unit configured to determine the number of pieces of power equipment order prediction information included in the power equipment order prediction information set as an order prediction information amount; a second generation unit configured to generate supply-side delivery detection information based on the delivery amount upper limit value and the order prediction information amount; and the adjusting unit is configured to adjust the distribution resources of the power equipment supply end according to the supply end distribution detection information.
In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors causes the one or more processors to implement the method described in any of the implementations of the first aspect above.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
The above embodiments of the present disclosure have the following advantageous effects: by the distribution resource adjustment method of some embodiments of the present disclosure, the waste of transportation resources is reduced. Specifically, the reason why the waste of transportation resources is easily caused is that: the transportation vehicles are directly added, and when the number of orders of the power equipment is small, the transportation resources are easy to waste. Based on this, the distribution resource adjustment method of some embodiments of the present disclosure first obtains a power equipment order information set that is distributed by a power equipment supply terminal in a preset period of time. And secondly, generating a power equipment order prediction information set based on the power equipment order information set. Wherein the power equipment order information in the power equipment order information set corresponds to the power equipment order prediction information in the power equipment order prediction information set. Thus, the power equipment order information set in the corresponding time period can be predicted through the acquired current power equipment order information set. Then, the upper limit value of the distribution amount corresponding to the power equipment supply end is determined. Then, the amount of the power equipment order prediction information included in the above-described power equipment order prediction information set is determined as an order prediction information amount. And then, generating supply end distribution detection information according to the distribution amount upper limit value and the order prediction information amount. Thus, it is possible to determine whether the power equipment supply terminal has the ability to deliver the power equipment within the current range by determining the relationship between the delivery amount upper limit value of the power equipment supply terminal and the predicted order prediction information amount. And finally, adjusting the distribution resources of the power equipment supply end according to the supply end distribution detection information. Therefore, the distribution resources of the power equipment supply end can be adjusted according to the distribution detection information of the supply end. And because the power equipment order prediction information set in the corresponding time period is predicted, the order prediction information amount in the corresponding time period is known in advance, so that the distribution resources can be adjusted in advance, and the waste of transportation resources is reduced.
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The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.
FIG. 1 is a flow chart of some embodiments of a method of adjusting a distribution resource according to the present disclosure;
FIG. 2 is a schematic diagram of the structure of some embodiments of a dispensing resource adjustment device according to the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a flow chart of some embodiments of a method of adjusting delivery resources according to the present disclosure. A flow 100 of some embodiments of a delivery resource adjustment method according to the present disclosure is shown. The distribution resource adjusting method comprises the following steps:
step 101, acquiring an order information set of the power equipment, which is distributed by the power equipment supply end in a preset time period.
In some embodiments, the execution body (for example, the computing device) of the distribution resource adjustment method may acquire, from the terminal, a power device order information set distributed by the power device supply end in a preset period of time through a wired connection or a wireless connection. The power plant supply may refer to a supply that produces power plants. For example, the power device may be a transformer, a circuit breaker. The power equipment order information may include: distribution address, power device name, number of power devices, latest distribution time.
Step 102, generating a power equipment order prediction information set based on the power equipment order information set.
In some embodiments, the executing entity may generate the power equipment order forecast information set based on the power equipment order information set. Wherein the power equipment order information in the power equipment order information set corresponds to the power equipment order prediction information in the power equipment order prediction information set. In practice, each piece of power equipment order information may be input into a pre-trained power equipment order prediction model to generate power equipment order prediction information, resulting in a power equipment order prediction information set. The pre-trained power equipment order prediction model may be a neural network model which is pre-trained and takes the power equipment order information as input and takes the power equipment order prediction information as output. For example, the power plant order prediction model may be a CNN (Convolutional Neural Networks, convolutional neural network) model, an RNN (Recurrent Neural Network ) model, or a DNN (Deep Neural Networks, deep neural network) model.
In practice, the above-described executing entity may generate the power equipment order forecast information set by:
first, a power equipment order sample set is obtained. The power equipment order specimens in the power equipment order specimen group may include specimen power equipment order information and specimen labels.
And a second step of selecting a power equipment order sample from the power equipment order sample group. The power equipment order sample may be randomly selected from the power equipment order sample group.
And thirdly, inputting the power equipment order sample into an initial power equipment order prediction model to obtain sample power equipment order prediction information. The initial power plant order prediction model may refer to an untrained convolutional neural network model.
And a fourth step of determining a loss value between a sample label included in the power equipment order sample and the sample power equipment order prediction information based on a preset loss function. Preset loss functions include, but are not limited to: mean square error loss function (MSE), cross entropy loss function (cross entropy), etc.
And fifthly, determining the initial power equipment order prediction model as a power equipment order prediction model in response to determining that the loss value is smaller than or equal to a preset loss value.
And sixthly, inputting the power equipment order information set into the power equipment order prediction model to obtain the power equipment order prediction information set. That is, each of the power equipment order information sets may be input into the power equipment order prediction model to generate power equipment order prediction information, resulting in a power equipment order prediction information set.
Step 103, determining the upper limit value of the distribution amount corresponding to the power equipment supply end.
In some embodiments, the executing body may determine an upper limit value of the delivery amount corresponding to the power equipment supply end. The upper limit of the delivery amount may be the maximum order delivery amount at a time at the power equipment supply end. For example, the distribution amount upper limit value may be obtained from the terminal of the power equipment supply end described above.
Step 104, determining the quantity of the power equipment order prediction information included in the power equipment order prediction information set as the order prediction information quantity.
In some embodiments, the executing entity may determine the amount of power equipment order forecast information included in the power equipment order forecast information set as the order forecast information amount.
And 105, generating supply end distribution detection information according to the distribution amount upper limit value and the order prediction information amount.
In some embodiments, the execution entity may generate the supply-side delivery detection information based on the delivery volume upper limit value and the order prediction information volume.
In practice, the executing entity may generate the supply-end delivery detection information by:
in response to determining that the delivery amount upper limit value is smaller than the order prediction information amount, the first step generates supply-end delivery detection information indicating that the delivery amount is insufficient.
And a second step of generating supply-end delivery detection information indicating that the delivery amount is satisfied in response to determining that the delivery amount upper limit value is equal to the order prediction information amount.
And a third step of generating supply-end delivery detection information indicating that the delivery amount is excessive in response to determining that the delivery amount upper limit value is greater than the order prediction information amount.
And 106, adjusting the distribution resources of the power equipment supply end according to the supply end distribution detection information.
In some embodiments, the executing entity may adjust the delivery resource of the power device supply according to the supply delivery detection information.
In practice, the execution body may adjust the distribution resources of the power equipment supply end through the following steps:
in response to determining that the supply-side distribution detection information indicates that the distribution amount is insufficient, the distribution amount upper limit value pieces of power equipment order prediction information, including the distribution address shortest from the power equipment supply side, are selected from the power equipment order prediction information set as target power equipment order prediction information sets. That is, the distance between the distribution address and the place where the power equipment supply terminal is located may be determined first.
And a second step of removing each piece of power equipment order prediction information corresponding to the target power equipment order prediction information group in the power equipment order prediction information set to obtain a remaining power equipment order prediction information group. That is, the power equipment order forecast information set from which the respective power equipment order forecast information corresponding to the target power equipment order forecast information set described above is removed may be determined as the remaining power equipment order forecast information set.
And thirdly, acquiring the transport end address information of each alternative transport end associated with the power equipment supply end, and obtaining a transport end address information group. That is, the transport end address information of the candidate transport ends of the respective third parties for transporting the electric power equipment, which cooperate, may be obtained from the electric power equipment supply end by means of wired connection or wireless connection. For example, the alternative transport end may be an express company. The transport end address information may represent an address of an alternative transport end.
Fourth, for each piece of surplus power equipment order prediction information in the surplus power equipment order prediction information group, the following processing steps are performed:
and a first sub-step of selecting, as target transporter address information, transporter address information closest to the delivery address included in the surplus power equipment order prediction information from the transporter address information group.
And a second sub-step of determining a distance between the delivery address included in the surplus power equipment order prediction information and the transportation end address information as a transportation distance.
And a third sub-step of determining whether the remaining power equipment order prediction information allows the modification of the delivery time in response to determining that the transportation distance is greater than a preset transportation distance. That is, it is determined whether or not a field capable of changing the distribution time is described in the surplus power facility order prediction information.
And a fourth sub-step of increasing the vehicle distribution resources of the power equipment supply terminal in response to determining that the remaining power equipment order prediction information does not allow the distribution time to be changed. That is, the distribution vehicles at the power equipment supply end can be increased.
The related matters in the first step to the fourth step are taken as an invention point of the present disclosure, and the second problem of "causing delivery delay" mentioned in the background art is solved. The factors responsible for the delivery delay are often as follows: the relationship between the delivery distance of the supply end and the delivery address of the order is not considered, so that the supply end cannot deliver in time. If the above factors are solved, the effect of avoiding the delivery delay can be achieved. To achieve this, first, in response to determining that the supply-side distribution detection information indicates that the distribution amount is insufficient, the power equipment order prediction information including the distribution amount upper limit value, the distribution address of which is shortest from the power equipment supply side, is selected from the power equipment order prediction information set as the target power equipment order prediction information set. Thus, orders with a longer delivery distance can be selected. And then, removing all the power equipment order prediction information corresponding to the target power equipment order prediction information group in the power equipment order prediction information set to obtain a residual power equipment order prediction information group. And then, acquiring the transport end address information of each alternative transport end associated with the power equipment supply end to obtain a transport end address information group. Therefore, the similar transportation end is convenient to select and used for transporting the power equipment corresponding to the order forecast information of the residual power equipment. Then, for each of the above-described remaining power equipment order prediction information groups, the following processing steps are performed: selecting the most recent transportation end address information from the transportation end address information group, which is closest to the delivery address included in the surplus power equipment order prediction information, as target transportation end address information; determining a distance between a delivery address included in the surplus power equipment order prediction information and the transportation end address information as a transportation distance; determining whether the remaining power equipment order forecast information allows modification of the delivery time in response to determining that the transportation distance is greater than a preset transportation distance; and in response to determining that the remaining power plant order forecast information does not allow modification of the delivery time, increasing vehicle delivery resources at the power plant supply. Therefore, the vehicle distribution resources of the power equipment supply end can be timely adjusted, and the timeliness of power equipment distribution is guaranteed.
Optionally, in response to determining that the transportation distance is less than or equal to the preset transportation distance, the surplus power equipment order prediction information is allocated to an alternative transportation end corresponding to the target transportation end address information.
In some embodiments, the executing entity may allocate the surplus power equipment order prediction information to the candidate transportation end corresponding to the target transportation end address information in response to determining that the transportation distance is equal to or less than the preset transportation distance.
Optionally, according to the order prediction information of the surplus power equipment, adjusting the distribution resources of the alternative transportation end corresponding to the target transportation end address information.
In some embodiments, the executing entity may adjust the delivery resource of the alternative transportation end corresponding to the target transportation end address information according to the residual power equipment order prediction information.
In practice, the executing body may adjust the delivery resources of the alternative transport end corresponding to the target transport end address information through the following steps:
and a first step of determining a delivery address included in the surplus power equipment order prediction information as a target delivery address.
And a second step of adding the target delivery address to the delivery area information of the alternative transportation end to obtain updated delivery area information.
And thirdly, updating the distribution radius and the distribution range of the alternative transportation end according to the updated distribution area information. For example, the delivery radius and the delivery range of the alternative delivery end may be enlarged according to the updated delivery area information.
With further reference to fig. 2, as an implementation of the method illustrated in the above figures, the present disclosure provides some embodiments of a delivery resource adjustment device, which correspond to those method embodiments illustrated in fig. 1, and which are particularly applicable to various electronic devices.
As shown in fig. 2, the delivery resource adjustment device 200 of some embodiments includes: an acquisition unit 201, a first generation unit 202, a first determination unit 203, a second determination unit 204, a second generation unit 205, and an adjustment unit 206. Wherein, the acquiring unit 201 is configured to acquire an order information set of the electric power equipment distributed by the electric power equipment supply end in a preset time period; a first generating unit 202 configured to generate a power equipment order prediction information set based on the power equipment order information set, wherein power equipment order information in the power equipment order information set corresponds to power equipment order prediction information in the power equipment order prediction information set; a first determining unit 203 configured to determine an upper limit value of the distribution amount corresponding to the power equipment supply end; a second determining unit 204 configured to determine the number of pieces of power equipment order prediction information included in the above-described power equipment order prediction information set as an order prediction information amount; a second generation unit 205 configured to generate supply-side delivery detection information based on the delivery amount upper limit value and the order prediction information amount; and an adjustment unit 206 configured to adjust the distribution resources of the power equipment supply terminal according to the supply terminal distribution detection information.
It will be appreciated that the elements described in the dispensing resource adjustment device 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above with respect to the method are equally applicable to the dispensing resource adjusting device 200 and the units contained therein, and are not described herein.
Referring now to fig. 3, a schematic diagram of an electronic device (e.g., computing device) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), car terminals (e.g., car navigation terminals), and the like, as well as stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.
As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM302, and the RAM303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.
It should be noted that, the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring an order information set of the power equipment, which is distributed by a power equipment supply end in a preset time period; generating a power equipment order prediction information set based on the power equipment order information set, wherein the power equipment order information in the power equipment order information set corresponds to the power equipment order prediction information in the power equipment order prediction information set; determining a distribution upper limit value corresponding to the power equipment supply end; determining the quantity of the power equipment order prediction information included in the power equipment order prediction information set as an order prediction information quantity; generating supply end distribution detection information according to the distribution quantity upper limit value and the order forecast information quantity; and adjusting the distribution resources of the power equipment supply end according to the supply end distribution detection information.
Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor comprising: the device comprises an acquisition unit, a first generation unit, a first determination unit, a second generation unit and an adjustment unit. The names of these units do not constitute a limitation on the unit itself in some cases, and for example, the first generating unit may also be described as "a unit that generates a power equipment order prediction information set based on the above power equipment order information set, where the power equipment order information in the above power equipment order information set corresponds to the power equipment order prediction information in the above power equipment order prediction information set".
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.
Claims (6)
1. A method of adjusting a distribution resource, comprising:
acquiring an order information set of the power equipment, which is distributed by a power equipment supply end in a preset time period;
generating a power equipment order prediction information set based on the power equipment order information set, wherein power equipment order information in the power equipment order information set corresponds to power equipment order prediction information in the power equipment order prediction information set;
determining a distribution upper limit value corresponding to the power equipment supply end;
determining the amount of power equipment order forecast information included in the power equipment order forecast information set as an order forecast information amount;
generating supply end distribution detection information according to the distribution quantity upper limit value and the order forecast information quantity;
according to the distribution detection information of the supply end, the distribution resources of the supply end of the power equipment are adjusted;
wherein, the adjusting the distribution resource of the power equipment supply end according to the supply end distribution detection information includes:
in response to determining that the supply-side distribution detection information indicates insufficient distribution amount, selecting, as a target power equipment order prediction information group, power equipment order prediction information having a distribution address that is shortest from the power equipment supply side from the power equipment order prediction information set;
removing all power equipment order prediction information corresponding to the target power equipment order prediction information group in the power equipment order prediction information set to obtain a residual power equipment order prediction information group;
acquiring transport end address information of each alternative transport end associated with the power equipment supply end to obtain a transport end address information group;
for each remaining power equipment order forecast information in the remaining power equipment order forecast information set, performing the following processing steps:
selecting the transportation end address information closest to the delivery address included in the surplus power equipment order prediction information from the transportation end address information group as target transportation end address information;
determining a distance between a delivery address included in the surplus power equipment order prediction information and the transportation end address information as a transportation distance;
responsive to determining that the shipping distance is greater than a preset shipping distance, determining whether the remaining power equipment order forecast information allows modification of delivery time;
responsive to determining that the remaining power equipment order forecast information does not allow modification of delivery time, increasing vehicle delivery resources of the power equipment supply;
in response to determining that the transportation distance is less than or equal to the preset transportation distance, distributing the residual power equipment order prediction information to an alternative transportation end corresponding to the target transportation end address information;
according to the surplus power equipment order prediction information, adjusting the distribution resources of the alternative transportation end corresponding to the target transportation end address information;
the adjusting the distribution resources of the alternative transportation end corresponding to the target transportation end address information according to the surplus power equipment order prediction information comprises the following steps:
determining a delivery address included in the surplus power equipment order prediction information as a target delivery address;
adding the target delivery address to the delivery area information of the alternative transport end to obtain updated delivery area information;
and updating the distribution radius and the distribution range of the alternative transportation end according to the updated distribution area information.
2. The method of claim 1, wherein the generating a power equipment order forecast information set based on the power equipment order information set comprises:
acquiring a power equipment order sample group;
selecting a power equipment order sample from the power equipment order sample group;
inputting the power equipment order sample into an initial power equipment order prediction model to obtain sample power equipment order prediction information;
determining a loss value between a sample label included in the power equipment order sample and the sample power equipment order prediction information based on a preset loss function;
in response to determining that the loss value is less than or equal to a preset loss value, determining the initial power equipment order prediction model as a power equipment order prediction model;
and inputting the power equipment order information set into the power equipment order prediction model to obtain the power equipment order prediction information set.
3. The method of claim 1, wherein the generating supply-side delivery detection information from the delivery amount upper limit value and the order prediction information amount includes:
generating supply-side delivery detection information representing an insufficient delivery amount in response to determining that the delivery amount upper limit value is smaller than the order prediction information amount;
generating supply-side delivery detection information representing that the delivery amount is satisfied in response to determining that the delivery amount upper limit value is equal to the order prediction information amount;
and generating supply end delivery detection information representing excess delivery quantity in response to determining that the delivery quantity upper limit value is greater than the order prediction information quantity.
4. A delivery resource adjustment device, comprising:
an acquisition unit configured to acquire a power equipment order information set distributed by a power equipment supply end within a preset time period;
a first generation unit configured to generate a power equipment order prediction information set based on the power equipment order information set, wherein power equipment order information in the power equipment order information set corresponds to power equipment order prediction information in the power equipment order prediction information set;
a first determination unit configured to determine an upper limit value of a delivery amount corresponding to the power equipment supply end;
a second determination unit configured to determine the amount of power equipment order prediction information included in the power equipment order prediction information set as an order prediction information amount;
a second generation unit configured to generate supply-side delivery detection information based on the delivery amount upper limit value and the order prediction information amount;
an adjusting unit configured to adjust the distribution resources of the power equipment supply end according to the supply end distribution detection information; an adjustment unit further configured to:
in response to determining that the supply-side distribution detection information indicates insufficient distribution amount, selecting, as a target power equipment order prediction information group, power equipment order prediction information having a distribution address that is shortest from the power equipment supply side from the power equipment order prediction information set;
removing all power equipment order prediction information corresponding to the target power equipment order prediction information group in the power equipment order prediction information set to obtain a residual power equipment order prediction information group;
acquiring transport end address information of each alternative transport end associated with the power equipment supply end to obtain a transport end address information group;
for each remaining power equipment order forecast information in the remaining power equipment order forecast information set, performing the following processing steps:
selecting the transportation end address information closest to the delivery address included in the surplus power equipment order prediction information from the transportation end address information group as target transportation end address information;
determining a distance between a delivery address included in the surplus power equipment order prediction information and the transportation end address information as a transportation distance;
responsive to determining that the shipping distance is greater than a preset shipping distance, determining whether the remaining power equipment order forecast information allows modification of delivery time;
responsive to determining that the remaining power equipment order forecast information does not allow modification of delivery time, increasing vehicle delivery resources of the power equipment supply;
in response to determining that the transportation distance is less than or equal to the preset transportation distance, distributing the residual power equipment order prediction information to an alternative transportation end corresponding to the target transportation end address information;
according to the surplus power equipment order prediction information, adjusting the distribution resources of the alternative transportation end corresponding to the target transportation end address information;
the adjusting the distribution resources of the alternative transportation end corresponding to the target transportation end address information according to the surplus power equipment order prediction information comprises the following steps:
determining a delivery address included in the surplus power equipment order prediction information as a target delivery address;
adding the target delivery address to the delivery area information of the alternative transport end to obtain updated delivery area information;
and updating the distribution radius and the distribution range of the alternative transportation end according to the updated distribution area information.
5. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-3.
6. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1-3.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109426885A (en) * | 2017-08-28 | 2019-03-05 | 北京小度信息科技有限公司 | Order allocation method and device |
| CN110766280A (en) * | 2019-09-20 | 2020-02-07 | 南京领行科技股份有限公司 | Vehicle scheduling method and generation method and device of target order prediction model |
| CN114386908A (en) * | 2022-01-11 | 2022-04-22 | 拉扎斯网络科技（上海）有限公司 | Transport capacity scheduling method and device, storage medium and equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20050288989A1 (en) * | 2004-06-24 | 2005-12-29 | Ncr Corporation | Methods and systems for synchronizing distribution center and warehouse demand forecasts with retail store demand forecasts |
| US20080162270A1 (en) * | 2006-12-29 | 2008-07-03 | Edward Kim | Method and system for forecasting future order requirements |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109426885A (en) * | 2017-08-28 | 2019-03-05 | 北京小度信息科技有限公司 | Order allocation method and device |
| CN110766280A (en) * | 2019-09-20 | 2020-02-07 | 南京领行科技股份有限公司 | Vehicle scheduling method and generation method and device of target order prediction model |
| CN114386908A (en) * | 2022-01-11 | 2022-04-22 | 拉扎斯网络科技（上海）有限公司 | Transport capacity scheduling method and device, storage medium and equipment |
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