CN117332934A - Parameter configuration method, device, electronic equipment and medium - Google Patents

Parameter configuration method, device, electronic equipment and medium Download PDF

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CN117332934A
CN117332934A CN202210724127.2A CN202210724127A CN117332934A CN 117332934 A CN117332934 A CN 117332934A CN 202210724127 A CN202210724127 A CN 202210724127A CN 117332934 A CN117332934 A CN 117332934A
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efficiency
sorting
target
delivery
configuration
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韩昊
吕祥东
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Beijing Jizhijia Technology Co Ltd
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Beijing Jizhijia Technology Co Ltd
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Abstract

The invention provides a parameter configuration method, a device, electronic equipment and a medium, which are applied to a goods warehouse-crossing system, wherein the method comprises the following steps: in a cargo sorting link, acquiring a first configuration parameter affecting cargo sorting efficiency, wherein the cargo sorting efficiency characterizes the number of inventory containers for completing sorting tasks in unit time; in a cargo delivery link, acquiring a second configuration parameter affecting cargo delivery efficiency, wherein the cargo delivery efficiency characterizes the number of order containers for completing delivery tasks in unit time; and determining target sorting efficiency and target delivery efficiency according to the first configuration parameters and the second configuration parameters, wherein the target sorting efficiency and the target delivery efficiency are matched. In this case, the sum of sorting cost and shipping cost obtained in the joint arrangement is the smallest, and the production efficiency is the highest.

Description

Parameter configuration method, device, electronic equipment and medium
Technical Field
The present invention relates to the field of warehouse logistics technologies, and in particular, to a parameter configuration method, a device, an electronic apparatus, and a medium.
Background
By cross stacking, it is meant that the goods "flow" directly from the receiving process to the delivery process, through the warehouse, with minimal handling and storage operations during which time from receiving to delivery is reduced, reducing warehouse storage space occupation. The more stock sort for store orders refers to: the goods from the whole vehicle from each supplier are received at the warehouse-crossing facility, disassembled, classified and piled up immediately according to the demands of each store and delivery points, and loaded on the prepared delivery tool, and the goods are delivered to the delivery points of each customer by the delivery tool. Wherein none of the goods enters the storage space of the warehouse.
The whole production flow of automatic warehouse-crossing sorting can be divided into: and the links of receiving, stacking, sorting, collecting and delivering and the like. In the delivery link, the following factors need to be considered first:
first, time of receipt and time of transportation: in order to ensure normal business and avoid operation damage caused by backorders, each store needs to combine the time required by the transportation route and completes transportation before the receiving time.
Second, optimal combination on each store path: often a truck will deliver goods for multiple stores, the optimal combination will be optimized based on travel issues (travel SalesmanProblem, TSP) to select a combination that requires a relatively shorter total shipping distance for delivery for the entire store.
Third, traffic volume and vehicle load of each store: since the number of products to be restocked in each store often varies, the actual vehicle capacity is matched according to the traffic volume of each store in order to ensure the loading capacity of each vehicle.
In the planning strategy and the consideration, the default warehouse-crossing sorting operation is to make a delivery and receiving plan through the optimal matching of paths, stores, vehicles and cargoes under the condition of fixed cost. However, in actual operation, when the sorting operation cost is ignored, higher production efficiency is pursued, which results in corresponding improvement of the sorting cost, and further, the overall sorting operation cost is improved.
Disclosure of Invention
The invention provides a parameter configuration method, a parameter configuration device, electronic equipment and a parameter configuration medium, which are used for realizing optimal configuration of resources, ensuring production efficiency and simultaneously minimizing cost. Specifically, the embodiment of the invention discloses the following technical scheme:
in a first aspect, an embodiment of the present invention provides a parameter configuration method, which is applied to a database-crossing management system, where the method includes: in a cargo sorting link, acquiring a first configuration parameter affecting cargo sorting efficiency, wherein the cargo sorting efficiency characterizes the number of inventory containers for completing sorting tasks in unit time; in a cargo delivery link, acquiring a second configuration parameter affecting cargo delivery efficiency, wherein the cargo delivery efficiency characterizes the number of order containers for completing delivery tasks in unit time; and determining target sorting efficiency and target shipping efficiency according to the first configuration parameters and the second configuration parameters, wherein the target sorting efficiency and the target shipping efficiency are matched.
Wherein the first configuration parameter comprises at least one of: robot number, field area, workstation number, shelf material throwing number and field layout; the second configuration parameters include at least one of: the number of trucks, the type of truck, the number of manpower, and the number of shipping mileage.
With reference to the first aspect, in a possible implementation manner of the first aspect, determining the target sorting efficiency and the target shipping efficiency based on the first configuration parameter and the second configuration parameter includes:
drawing an electronic map of the warehouse crossing warehouse by using simulation software according to the first configuration parameters, wherein the electronic map comprises field areas, the number of workstations, goods shelf material delivery and field layout; service parameters are configured according to the content of the electronic map, and the service parameters comprise: robot number, order number, inventory usage and workstation picking period; performing simulation operation on the electronic map input with the configuration parameters by using the simulation software to obtain at least one sorting efficiency, wherein in the simulation operation process, one sorting efficiency is correspondingly obtained when one value of the service parameters is regulated; and determining the target sorting efficiency and the target delivery efficiency according to the at least one sorting efficiency and the service level of the at least one store delivery task.
With reference to the first aspect, in another possible implementation manner of the first aspect, determining the target sorting efficiency and the target shipping efficiency according to the at least one sorting efficiency and a service level of at least one store shipping task includes: obtaining production time consumption corresponding to each sorting efficiency during simulation operation; determining the target sorting efficiency and the target shipping efficiency based on each of the production time consumption and the service level.
With reference to the first aspect, in a further possible implementation manner of the first aspect, determining the target sorting efficiency and the target shipping efficiency according to each of the production time consumption and the service level includes: determining the target sorting efficiency in the at least one sorting efficiency, wherein the target sorting efficiency corresponds to first production time, and calculating the target shipping efficiency according to the first production time and the service level, wherein the service level comprises shipping time through a vehicle path planning problem YRP or a carrier problem TSP.
With reference to the first aspect, in a further possible implementation manner of the first aspect, the method further includes: and setting all parameters in a goods sorting link and a delivery link according to the first configuration parameters and the second configuration parameters, and executing the current sorting task and the current delivery task.
In a second aspect, an embodiment of the present invention further provides a parameter configuration apparatus, where the apparatus includes:
the system comprises an acquisition unit, a storage unit and a control unit, wherein the acquisition unit is used for acquiring a first configuration parameter affecting the cargo sorting efficiency in a cargo sorting link, and the cargo sorting efficiency represents the number of inventory containers for completing sorting tasks in unit time; and in the link of goods delivery, acquiring a second configuration parameter affecting the efficiency of goods delivery, wherein the efficiency of goods delivery characterizes the number of order containers for completing delivery tasks in unit time;
And the determining unit is used for determining target sorting efficiency and target delivery efficiency according to the first configuration parameters and the second configuration parameters, and the target sorting efficiency is matched with the target delivery efficiency.
With reference to the second aspect, in a possible implementation manner of the second aspect, the determining unit includes:
the drawing unit is used for drawing an electronic map of the warehouse crossing warehouse by using simulation software according to the first configuration parameters, wherein the electronic map comprises field areas, the number of workstations, goods shelf material delivery and field layout;
the configuration unit is used for configuring service parameters according to the content of the electronic map, and the service parameters comprise: robot number, order number, inventory usage and workstation picking period;
the simulation unit is used for carrying out simulation operation on the electronic map input with the configuration parameters by using the simulation software to obtain at least one sorting efficiency, and one sorting efficiency is correspondingly obtained when one value of the service parameters is regulated in the simulation operation process;
and the determining subunit is used for determining the target sorting efficiency and the target delivery efficiency according to the at least one sorting efficiency and the service level of the at least one store delivery task.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: a processor and a memory for storing computer-executable instructions; the processor is configured to read the instructions from the memory and execute the instructions to implement the method of the foregoing first aspect and various implementations of the first aspect.
Furthermore, a computer readable storage medium is provided, storing computer program instructions which, when read by a computer, perform the method of the foregoing first aspect and various implementations of the first aspect.
According to the parameter configuration method, the device, the electronic equipment and the medium, the target sorting efficiency and the target delivery efficiency are determined according to the first configuration parameter in the sorting link and the second configuration parameter in the delivery link, and the two efficiencies are matched, so that the sum of the sorting cost and the delivery cost is minimum when combined arrangement is achieved, and under the parameter configuration, the goods sorting efficiency and the delivery efficiency are guaranteed, and the advantage of lowest overall total production cost is achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a cross-library architecture according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for configuring parameters according to an embodiment of the present invention;
FIG. 3a is a graph showing a first production efficiency versus sorting cost according to an embodiment of the present invention;
FIG. 3b is a graph showing a second production efficiency versus shipping cost provided by an embodiment of the present invention;
FIG. 4 is a graph showing the overall cost and the production efficiency according to the embodiment of the present invention;
FIG. 5 is a schematic diagram of a layout of a library-crossing system according to an embodiment of the present invention;
FIG. 6 is a flowchart of another parameter configuration method according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a parameter configuration device according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a determining unit according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solution in the embodiments of the present application and make the above objects, features and advantages of the embodiments of the present application more obvious, the technical solution in the embodiments of the present application is described in further detail below with reference to the accompanying drawings.
Before the technical scheme of the embodiment of the application is described, an application scenario of the embodiment of the application is described with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a schematic diagram of a cargo warehouse system architecture according to an embodiment of the present application. The system 100 includes: server 10, robot 20, shelf area 30, workstation 40, sorters 42, store collection 50, and truck area 60. Other devices, not shown in fig. 1, such as personnel and a console may also be included in the system 100.
The server 10 may be one server or may be a plurality of servers, such as a server cluster, for controlling the operation of other devices/robots in the database system. One or more robots 20 are used to rack goods to the shelf regions 30. A plurality of shelves are provided in the shelf area 30, and a plurality of stock containers 31 are placed on each shelf, and the stock containers 31 refer to containers in which goods which have not been sorted are stored in the process of producing the stock containers. Optionally, a plurality of inventory receptacles 31 are arranged in an array in the shelf area 30.
The server 10 communicates with the robots 20 through wireless network, and each robot 20 performs a handling task of a corresponding stock container under the control of the server 10. For example, the server 10 instructs the robot 20 to carry the inventory receptacles 31 on the shelf area 30 to at least one workstation 40 in a preset travel path to cause the sorters 42 in the workstation 40 to complete the sorting task.
The sorting personnel 42 in the workstation 40 sorts the goods in the incoming at least one stock container 31, after sorting, the goods/goods required in all tasks are placed in the corresponding order containers 41, a turnover box is generated and stored in the store set 50, and finally the stock containers corresponding to the stores in the store set 50 are distributed to the corresponding stores or superbars through at least one truck in the truck area 60.
Wherein the order container 41 refers to a container to which an order is bound during the over-warehouse production process to be sorted, or sorted. In addition, after the sorting task is completed, the robot 20 returns the stock containers to the shelf area 30 again, and waits for the transfer task of other stock containers.
In an automated over-warehouse sorting process, the sorting cost and shipping cost are mutually affected. For example, at an end store or at an end facility, there is a service agreement, such as the requirement: the first stock keeping unit (Stock Keeping Unit, sku_1) needs to be sent to the designated store 1 10 a day, or sku_2 can only be sent to the designated store 2 after 10 a day, or sku_3 must be sent to the designated store 3 simultaneously with sku_4, etc., then service level agreements (service level agreement, SLA) need to be considered and achieved in the sorting and shipping process.
Alternatively, one implementation is to select/configure an order combination, such as by adding vehicles or speeding up, or waiting, to meet the SLA requirements. Another implementation way is to combine the operation of the upstream sorting task, set up: the sku_1 order needs to be placed in the holding area before 8 points, the sku_2 order needs to wait in the holding area until 10 points, and the constraints that the configuration of the sku_3 and sku_4 orders must complete sorting at the same time. However, the above implementation increases the total cost, and as a higher demand is placed on the sorting efficiency or the shipping efficiency, the sorting cost or the shipping cost increases, which eventually results in an increase in the total cost.
The embodiment of the application provides a joint production arrangement mode comprehensively considering sorting cost and shipping cost, and aims to limit sorting complexity to control the cost of the warehouse-crossing sorting automation equipment on the basis of determining production efficiency of the two costs and guaranteeing certain production efficiency, so that the cost efficiency maximization of the whole warehouse-crossing production is realized.
The following describes in detail the technical solutions provided in the embodiments of the present application.
The present embodiment provides a parameter configuration method, which can be applied to the server 10 in the above-mentioned library system, as shown in fig. 2, and the method includes:
Step 101: in a cargo sorting link, a first configuration parameter affecting cargo sorting efficiency is obtained, wherein the cargo sorting efficiency characterizes the number of stock containers for completing sorting tasks in unit time.
Wherein the first configuration parameters include: at least one of the number of robots, the area of the site, the number of workstations, the number of shelf material drops and the site layout. In addition, parameters such as order quantity, inventory status, and workstation pick cycle may also be included. Specifically, the number of robots includes the number of robots used in the sorting work process, including a robot that transports goods, a robot that performs sorting tasks, and the like. The area of the site is the area of the surmounting system and the number of workstations is the number of workstations 40 described above and shown in fig. 1. The shelf material delivery quantity refers to the quantity of stock containers 31 stored in the shelf area; the site layout refers to a planning mode, a utilization rate and the like of each area in the more-warehouse site. For example, when the number of robots to be put in is increased or the number of workstations is increased, the sorting efficiency (i.e., first production efficiency) is improved, but the sorting cost is increased, whereas if the number of robots or workstations is reduced, the production efficiency is lowered and the sorting cost is lowered.
Other influencing factors may be included, such as, but not limited to, first production efficiency.
The first configuration parameters in step 101 may be set by software simulation, and the respective parameter values in the first configuration parameters may be freely set and modified.
Step 102: in the delivery link, a second configuration parameter is acquired that affects delivery efficiency of the goods, which characterizes the number of order containers that complete the delivery task per unit time.
Wherein the second configuration parameter comprises at least one of: the number of trucks, the type of truck, the number of manpower, and the number of shipping mileage. The number of trucks refers to the number of trucks for delivery, the type of trucks refers to the type of trucks for delivery, the manpower input refers to the personnel input number in the subsequent collecting and delivering links after the sorting task, and the transportation mileage refers to the freight rate corresponding to the distance from the trucks for delivery to a target store, including oil rate, parking rate and the like. In addition, the second configuration parameters may further include other more or less parameters, such as the number of stores, the number of orders, and the like, which is not limited in this embodiment. Similar to the previous step 101, the second configuration parameters in this step may also be set by software simulation.
In addition, the first configuration parameter and the second configuration parameter may be dynamically changed, so that the server obtains the first configuration parameter and the second configuration parameter in real time.
Step 103: and determining target sorting efficiency and target shipping efficiency according to the first configuration parameters and the second configuration parameters, wherein the target sorting efficiency and the target shipping efficiency are matched.
The sorting efficiency corresponding to the current moment, also called first production efficiency, can be obtained at the current moment according to the first configuration parameters; the corresponding shipping efficiency, also referred to as the second production efficiency, can be obtained according to the second configuration parameter at the current time. And, each production efficiency corresponds to a cost, e.g., a first production efficiency corresponds to a sorting cost and a second production efficiency corresponds to a shipping cost. Wherein the sorting costs are understood as production costs required for completing the sorting operation under the first configuration parameters, which production costs relate to e.g. the number of sorting robots, the site area costs, the layout costs and the shelf material delivery costs. Similarly, shipping costs may be understood as the production costs required to perform a shipping task under the second configuration parameters, including: the number of delivery trucks, the transportation cost, the labor input cost, the mileage and the like.
Further, the first production efficiency and the sorting cost may be represented by a first correspondence relationship, as shown in fig. 3a, representing a correspondence relationship between sorting cost and first production efficiency, wherein the horizontal axis represents the first production efficiency and the vertical axis represents the sorting cost. It can be seen that sorting costs increase with increasing first production efficiency.
Alternatively, the first correspondence is expressed as a mathematical expression: y1=f (E1), (1)
Wherein E1 is the first production efficiency, y1 is the sorting cost, and the relationship between the two is represented by expression (1).
Similarly, the second production efficiency and the shipping cost may be represented by a second correspondence, as shown in fig. 3b, which is a graph of the second correspondence, representing the correspondence between the shipping cost and the second production efficiency, wherein the horizontal axis represents the second production efficiency and the vertical axis represents the shipping efficiency. As can be seen, shipping production decreases with increasing second production efficiency. It is thereby achieved that there is a complementary relationship between the sorting costs associated with the first production costs and the delivery costs associated with the second production efficiency.
Alternatively, the second correspondence is expressed as a mathematical expression: y2=g (E2), (2)
Wherein E2 is the second production efficiency, y2 is the shipping cost, and the relationship between the two is represented by expression (2).
The determining of the target sorting efficiency and the target shipping efficiency in step 103 above, and the matching of the target sorting efficiency and the target shipping efficiency means that: determining a production efficiency in the first production efficiency and sorting cost curve as a target sorting efficiency; determining a production efficiency in the second production efficiency and shipping cost curve as a target shipping efficiency; and meets a target total cost minimum at the target sorting efficiency and the target shipping efficiency. The target total cost includes: and a sum of a target sorting cost and a target shipping cost, the target sorting cost corresponding to the target sorting efficiency, the target shipping cost corresponding to the target shipping efficiency.
For example, in one example, assuming that the target sorting efficiency is E11, the target sorting cost is determined to be y11 based on the above-described first correspondence; and determining the target delivery cost as Y21 according to the target delivery efficiency as E21 and the second corresponding relation, and further obtaining a target total cost Y as a data expression: y=y11+y21=f (e11) +g (E21), (3)
Optionally, based on the steps 101 and 102, it is determined that the target sorting efficiency and the target shipping efficiency in step 103 are the same or similar. For example, the first production efficiency is configured to be equal to the second production efficiency, that is, e11=e21, where the target total cost is Y, and is the sum of the target sorting cost Y11 and the target shipping cost Y21.
The target sorting efficiency and the target delivery efficiency are similar, namely, the two production efficiencies are different within a preset range, and the obtained target total cost is an acceptable value within the preset range and does not exceed a preset upper limit. Specifically, the preset range may be set according to the actual situation of the database system, which is not limited in this embodiment.
Referring to fig. 4, a graph between production efficiency and target total cost is provided for the present embodiment, and the graph can be obtained according to the graphs shown in fig. 3a and 3b, in which the horizontal axis represents production efficiency and the vertical axis represents target total cost Y. As shown in fig. 4, at the position a where the production efficiency e1=e2, the corresponding target total cost Y is minimum.
According to the method provided by the embodiment, the target sorting efficiency and the target delivery efficiency are determined according to the first configuration parameter in the sorting link and the second configuration parameter in the delivery link, and the two efficiencies are matched, so that the sum of the sorting cost and the delivery cost is minimum when the sorting cost and the delivery cost are combined, and under the parameter configuration, the sorting efficiency and the delivery efficiency of cargoes are guaranteed, and the beneficial effect of the lowest overall total production cost is achieved.
In this embodiment, the first production efficiency and the corresponding sorting cost, the second production efficiency and the corresponding shipping cost may be obtained by:
One possible implementation is by way of simulation.
Taking as an example the determination of the target sorting efficiency and the corresponding sorting costs according to a first configuration parameter, wherein the first configuration parameter specifically comprises a parameter related to the service (also called first service parameter), for example the first service parameter comprises: order quantity, inventory status, and workstation pick cycle, etc. The first business parameter may be understood as a sorting task amount that can be completed per unit time, such as 50 orders per hour, under certain configuration parameters, such as a robot number, a workstation number, a field area, etc., and the business parameter includes the order number 50.
And then, based on the first configuration parameter and the first service parameter, outputting sorting efficiency and sorting cost corresponding to the sorting efficiency through preset model operation.
The preset model may be an algorithm model or a simulation model, such as a agent-based simulation model. As shown in fig. 5, an electronic map of the warehouse is simulated by software simulation. At least one workstation, a shelf area and an empty area (see grey area in fig. 5) where the robot is movable are shown in the figure, step 103, as shown in fig. 6, specifically comprises:
Step 1031: and drawing an electronic map of the warehouse through simulation software according to the first configuration parameters, wherein the electronic map comprises field areas, the number of workstations, goods shelf material delivery and field layout.
Step 1032: service parameters are configured according to the content of the electronic map, and the service parameters comprise: robot number, order count, inventory usage, and workstation pick cycle.
Step 1033: and performing simulation operation on the electronic map input with the configuration parameters by using the simulation software to obtain at least one sorting efficiency, wherein in the simulation operation process, one sorting efficiency is correspondingly obtained when one value of the service parameters is regulated.
Step 1034: and determining the target sorting efficiency and the target delivery efficiency according to the at least one sorting efficiency and the service level of the at least one store delivery task.
In step 1032, one or more of the service parameters or configuration parameters are adjusted, for example, the "number of robots" in the first configuration parameter is gradually adjusted from 1 to the maximum number, each time the value of one parameter is adjusted, the operation can be simulated on software, after a plurality of time steps, the required order task is completed, and the simulated output result is obtained, where the output result includes the first production efficiency E1 and the corresponding first sorting cost y1, and a group of (E1, y 1) is obtained, and similarly, each parameter value is adjusted one by one, then after the software simulation, a plurality of simulation results are output, and all the simulation results form a simulation result set.
The first correspondence and the first relationship curve can be obtained from the simulation results obtained after the simulation.
Optionally, in the process of adjusting different parameter values and obtaining different simulation results through simulation operation, the same first production efficiency may be output after the preset model simulation operation under different configuration parameters and service parameters. For example, configuration 1: the first production efficiency E is obtained under the parameter configuration of the site area A, the number of workstations n1, the number of shelf materials put in n2, the number of robots n3 and the number of orders n4 1-1 . Configuration 2: the first production efficiency E is obtained under the parameter configuration of the site area A, the number of workstations n1, the number of shelf materials put in n2, the number of robots n5 and the number of orders n6 1-2 And a first production efficiency E 1-1 And E is 1-2 The same, for example, the first production efficiency obtained by both configuration parameters is 70%, and the minimum one of the corresponding sorting costs in the two first production efficiencies is reserved.
In this embodiment, under the simulation of configuration 1, the first production efficiency E is obtained by outputting 1-1 The corresponding sorting cost is y 1-1 The method comprises the steps of carrying out a first treatment on the surface of the Under the simulation of configuration 2, the first production efficiency E is obtained by output 1-2 The corresponding sorting cost is y 1-2 . Due to E 1-1 ＝E 1-2 In this case, therefore, the two sorting costs are compared, y 1-1 ＞y 1-2 Therefore, the scheme of the configuration 2 with the field area of A, the workstation number of n1, the storage rack material throwing number of n2, the robot number of n5 and the order number of n6 is selected, and the sorting cost corresponding to the scheme is lower.
At this time, a mapping relationship between the first production efficiency E1 and the sorting cost y1, which is a full shot, can be obtained. By "full shot" is understood: any element in Y is an image of an element in X, i.e. the corresponding first production efficiency E1 can be found at any value in the sorting cost Y.
Optionally, the determining the target sorting efficiency and the target shipping efficiency according to the at least one sorting efficiency and the service level of the at least one shop shipping task specifically includes: obtaining production time consumption corresponding to each sorting efficiency in simulation operation; the target sorting efficiency and the target shipping efficiency are determined based on each production time and service level.
Wherein, the production time is also called as a first production time period Ti, and each first production time period T corresponds to a first production efficiency Ei and also corresponds to a sorting cost yi. Each first production time period Ti represents the time period spent performing the sorting operation under any one of the first configuration parameters. Where i represents the ith simulation calculation. For example, in the above embodiment, the simulation result outputted by the simulation "configuration 1" includes the first production time period T1. The first production time period T1 is used to determine whether the service level SLA of the store is satisfied.
For example, the requirement scu_1 needs to be forwarded to the designated store 1 at 10 points per day, at this time, whether the requirement of forwarding to 10 points per day can be met may be determined according to the first production time period T1, for example, from the first production time period t1=1 hour (hor), the starting time T of the sorting task execution is 8 am, the time of completing the sorting task is 8+1=9 points, and then, in combination with the position, the transportation route and the time of store 1, the cost of forwarding the goods to store 1 before 10 points, that is, the shipping cost, is evaluated. The return cost may be calculated and assessed by a third party.
If the current sorting task is performed at 9 am, the time after the current sorting task is performed is 9+1=10, the shipping task sent to 10 points can not be completed, or other auxiliary tools are needed to realize the task, and the corresponding shipping cost increases.
In this embodiment, the first production efficiency is output through the simulation result, the time consumed in this production and the service level SLA required by the terminal store can be obtained, so that the delivery cost of the delivery end and the corresponding parameter ratio, such as the ratio between the delivery cost and the second production efficiency, can be obtained, and the second corresponding relationship and the second relationship curve can be obtained.
It should be understood that the proportioning condition of the shipping cost and the corresponding parameters may be calculated through another software simulation, or the quotation and the configuration condition may be provided by a third party, and the specific implementation of obtaining the shipping cost and the second production relationship is not limited in this embodiment.
Alternatively, another method of obtaining the shipping cost and the second production efficiency is by algorithmic calculation. Specifically, according to the first production efficiency E1 obtained in the sorting link, the first production time period Ti and the service level SLA required by the end store can be deduced, for example, the store 1 needs to complete delivery before 10 points, and the store 2 needs to complete delivery of goods after 10 points. The service level SLA includes a shipping time.
According to the above parameters, the first production time and service level SLA may be calculated to obtain the second production efficiency E2 and the target shipping efficiency according to the vehicle path planning problem (Vehicle Routing Problem, YRP) or the trip problem (Traveling Salesman Problem, TSP), and other related parameters, such as the number of trucks, the type of vehicles, the kilometers, etc., so as to obtain a second corresponding relationship, where the mapping relationship between the second production efficiency E2 and the shipping cost y2 in the second corresponding relationship is full shot.
In addition, the method further comprises the following steps: and setting all parameters in a goods sorting link and a delivery link according to the first configuration parameters and the second configuration parameters, and executing the current sorting task and the current delivery task. For example, according to the first configuration parameters, such as the number of robots, the area of the site, the number of workstations, the number of shelf materials put in, the site layout and the second configuration parameters, such as the number of vehicles, the type of vehicles, the number of manpower input, the kilometer land transportation cost and the like; and configuring a library-crossing system according to the first configuration parameters and the second configuration parameters.
For example, in the present embodiment, the first configuration parameter of the above-described "configuration 2" is determined as the target configuration parameter, and the number of vehicles 2, the vehicle type 2, the number of human inputs 2, and the kilometer land cost 2 included in the second configuration parameter are determined to be the parameter configurations that most match the current first configuration parameter, so that the total cost of configuration according to such first configuration parameter and second configuration parameter is minimized.
According to the method provided by the embodiment, under the condition of a given service level, the resource proportion with the smallest sum of sorting cost and delivery cost is searched, the problem that the cost of another link is increased due to the fact that a certain parameter is adjusted in a single sorting link or a delivery link is solved, for example, the service level time requirement is advanced due to the fact that the delivery end is provided with one more end point, the generation efficiency requirement of sorting is greatly improved, and the input cost of the sorting end is far greater than the cost of adding one vehicle to the delivery end.
When the variation of the in-store operation cost with efficiency is ignored, the maximum capacity requirement of the in-store operation is often increased. However, in practical applications, the required capacity of a large number of situations is lower than the actual maximum capacity in the warehouse, thereby causing redundancy of equipment in the warehouse and further causing waste of total cost. Therefore, according to the method provided by the embodiment, when the in-warehouse working efficiency is properly allowed to be reduced in the overall planning, although the corresponding delivery cost is improved, the cost reduction of the in-warehouse automatic sorting system can compensate the increase of the part of cost, so that the minimum overall sorting production cost is realized.
Embodiments of the apparatus corresponding to the foregoing method embodiments are described below.
Based on the method shown in fig. 2, the present embodiment further provides a parameter configuration device, which is configured to execute the parameter configuration method in the foregoing embodiment.
Specifically, as shown in fig. 7, the apparatus includes: an acquisition unit 701 and a determination unit 702. In addition, the apparatus may include other more or fewer units/modules, such as a storage unit, a receiving unit, a transmitting unit, and so on.
The acquiring unit 701 is configured to acquire, in a cargo sorting link, a first configuration parameter affecting cargo sorting efficiency, where the cargo sorting efficiency characterizes the number of inventory containers completing a sorting task in a unit time; and in the delivery link, acquiring a second configuration parameter affecting the delivery efficiency of the goods, wherein the delivery efficiency of the goods characterizes the number of order containers for completing the delivery task in unit time.
And a determining unit 702, configured to determine a target sorting efficiency and a target shipping efficiency according to the first configuration parameter and the second configuration parameter, where the target sorting efficiency and the target shipping efficiency are matched. Wherein a target total cost at the target sorting efficiency and the target shipping efficiency is minimized, the target total cost including a sum of a target sorting cost and a target shipping cost.
Optionally, the target sorting efficiency is the same as or similar to the target shipping efficiency.
Alternatively, in a specific implementation manner of this embodiment, as shown in fig. 8, the determining unit 702 includes:
and the drawing unit 7021 is used for drawing an electronic map of the warehouse with the over library by using simulation software according to the first configuration parameters, wherein the electronic map comprises field area, workstation number, shelf material delivery and field layout.
A configuration unit 7022, configured to configure service parameters according to the content of the electronic map, where the service parameters include: robot number, order count, inventory usage, and workstation pick cycle.
The simulation unit 7023 is configured to perform a simulation operation on the electronic map input with the configuration parameters by using the simulation software, so as to obtain at least one sorting efficiency, and each time a value in the service parameters is adjusted in the simulation operation process, a sorting efficiency is correspondingly obtained.
A determining subunit 7024, configured to determine the target sorting efficiency and the target shipping efficiency according to the at least one sorting efficiency and the service level of the at least one store shipping task.
Optionally, in another specific implementation manner of this embodiment, the simulation unit 7023 is further configured to obtain a production time consumption corresponding to each sorting efficiency during the simulation operation, and the determining subunit 7024 is further configured to determine the target sorting efficiency and the target shipping efficiency according to each production time consumption and the service level.
Optionally, in still another specific implementation manner of this embodiment, the determining subunit 7024 is further configured to determine the target sorting efficiency in at least one sorting efficiency, and calculate, according to the first production time and the service level, the target sorting efficiency through a vehicle path planning problem YRP or a carrier problem TSP, where the service level includes a shipping time, and the target sorting efficiency corresponds to the first production time.
Optionally, in another specific implementation manner of this embodiment, the configuration unit 7022 is further configured to set all parameters in the cargo sorting link and the shipping link according to the first configuration parameter and the second configuration parameter, and perform a current sorting task and a current shipping task.
According to the device provided by the embodiment, the target sorting efficiency and the target delivery efficiency are determined according to the first configuration parameter in the sorting link and the second configuration parameter in the delivery link, and the two efficiencies are matched, so that the sum of the sorting cost and the delivery cost is minimum when the sorting cost and the delivery cost are combined, and under the parameter configuration, the sorting efficiency and the delivery efficiency of cargoes are guaranteed, and the beneficial effect of the lowest overall total production cost is achieved.
In a specific implementation, the embodiment of the application further provides an electronic device, which may be a server in the foregoing embodiment, for implementing all or part of the steps of the method for determining the foregoing production efficiency.
Fig. 9 is a schematic structural diagram of an electronic device according to the present embodiment. Comprising the following steps: at least one processor 110, memory 120, and at least one interface 130, and may further include a communication bus 140 for connecting these components.
Wherein the at least one processor 110 may be a CPU or processing chip configured to read and execute computer program instructions stored in the memory 120 to enable the at least one processor 110 to perform the method flows of the various embodiments described above.
The memory 120 may be a non-transitory memory (non-transitory memory) that may include volatile memory, such as high-speed random access memory (RandomAccess Memory, RAM), or may include non-volatile memory, such as at least one disk memory.
At least one interface 130 includes an input-output interface, and a communication interface, which may be a wired or wireless interface, to enable a communication connection between the electronic device and other devices. The input-output interface may be used to connect peripheral devices such as a display screen, a keyboard, etc.
In some embodiments, the memory 120 stores computer readable program instructions that when read and executed by the processor 110 implement a method of determining production efficiency as in the previous embodiments.
Furthermore, the present embodiment also provides a computer program product for storing computer readable program instructions that, when executed by the processor 110, implement a method for determining production efficiency in the foregoing embodiment.
In addition, the embodiment also provides a cross-warehouse sorting system, which may be a cross-warehouse management system as shown in fig. 1, where the system includes: at least one inventory container, at least one order container, at least one workstation, at least one robot and server, a shipping truck, etc., wherein each of said inventory containers and each of said order containers are mounted on one of said robots; such robots include, but are not limited to, automated devices such as the above described automatically movable carriers, automatically carried robots, or stationary transport devices, among others.
The server may be an electronic device as shown in fig. 9 in the embodiment of the present application, and is configured to perform all or part of the steps in the method for determining the production efficiency in the foregoing embodiment. The specific process may refer to the description of the foregoing method embodiment, and this embodiment is not described herein in detail.
It should be noted that in the present application, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM).
Additionally, the computer-readable medium may even be paper or other suitable medium upon which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof.
In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
The above-described embodiments of the present application are not intended to limit the scope of the present application.

Claims (10)

1. A method of parameter configuration, the method comprising:
in a cargo sorting link, acquiring a first configuration parameter affecting cargo sorting efficiency, wherein the cargo sorting efficiency characterizes the number of inventory containers for completing sorting tasks in unit time;
in a cargo delivery link, acquiring a second configuration parameter affecting cargo delivery efficiency, wherein the cargo delivery efficiency characterizes the number of order containers for completing delivery tasks in unit time;
and determining target sorting efficiency and target shipping efficiency according to the first configuration parameters and the second configuration parameters, wherein the target sorting efficiency and the target shipping efficiency are matched.
2. The method of claim 1, wherein the first configuration parameter comprises at least one of: robot number, field area, workstation number, shelf material throwing number and field layout;
the second configuration parameters include at least one of: the number of trucks, the type of truck, the number of manpower, and the number of shipping mileage.
3. The method of claim 1 or 2, wherein determining a target sorting efficiency and a target shipping efficiency based on the first configuration parameter and the second configuration parameter comprises:
Drawing an electronic map of the warehouse crossing warehouse by using simulation software according to the first configuration parameters, wherein the electronic map comprises field areas, the number of workstations, goods shelf material delivery and field layout;
service parameters are configured according to the content of the electronic map, and the service parameters comprise: robot number, order number, inventory usage and workstation picking period;
performing simulation operation on the electronic map input with the configuration parameters by using the simulation software to obtain at least one sorting efficiency, wherein in the simulation operation process, one sorting efficiency is correspondingly obtained when one value of the service parameters is regulated;
and determining the target sorting efficiency and the target delivery efficiency according to the at least one sorting efficiency and the service level of the at least one store delivery task.
4. The method of claim 3, wherein determining the target sorting efficiency and the target shipping efficiency based on the at least one sorting efficiency and a service level of at least one store shipping task comprises:
obtaining production time consumption corresponding to each sorting efficiency during simulation operation;
determining the target sorting efficiency and the target shipping efficiency based on each of the production time consumption and the service level.
5. The method of claim 4, wherein determining the target sorting efficiency and the target shipping efficiency based on each of the production time elapsed and the service level comprises:
determining the target sorting efficiency among the at least one sorting efficiency, the target sorting efficiency corresponding to a first production time,
the target shipping efficiency is calculated from the first production time and the service level, including shipping time, via a vehicle path planning problem YRP or a traveler problem TSP.
6. The method according to any one of claims 1-5, further comprising:
and setting all parameters in a goods sorting link and a delivery link according to the first configuration parameters and the second configuration parameters, and executing the current sorting task and the current delivery task.
7. A parameter configuration apparatus, the apparatus comprising:
the system comprises an acquisition unit, a storage unit and a control unit, wherein the acquisition unit is used for acquiring a first configuration parameter affecting the cargo sorting efficiency in a cargo sorting link, and the cargo sorting efficiency represents the number of inventory containers for completing sorting tasks in unit time; and in the link of goods delivery, acquiring a second configuration parameter affecting the efficiency of goods delivery, wherein the efficiency of goods delivery characterizes the number of order containers for completing delivery tasks in unit time;
And the determining unit is used for determining target sorting efficiency and target delivery efficiency according to the first configuration parameters and the second configuration parameters, and the target sorting efficiency is matched with the target delivery efficiency.
8. The apparatus according to claim 7, wherein the determining unit includes:
the drawing unit is used for drawing an electronic map of the warehouse crossing warehouse by using simulation software according to the first configuration parameters, wherein the electronic map comprises field areas, the number of workstations, goods shelf material delivery and field layout;
the configuration unit is used for configuring service parameters according to the content of the electronic map, and the service parameters comprise: robot number, order number, inventory usage and workstation picking period;
the simulation unit is used for carrying out simulation operation on the electronic map input with the configuration parameters by using the simulation software to obtain at least one sorting efficiency, and one sorting efficiency is correspondingly obtained when one value of the service parameters is regulated in the simulation operation process;
and the determining subunit is used for determining the target sorting efficiency and the target delivery efficiency according to the at least one sorting efficiency and the service level of the at least one store delivery task.
9. An electronic device, comprising: a processor and a memory, wherein,
the memory is used for storing computer executable instructions;
the processor is configured to read the instructions from the memory and execute the instructions to implement the method of any one of claims 1 to 6.
10. A computer readable storage medium, characterized in that the storage medium stores computer program instructions,
when the computer reads the instructions, the method according to any of claims 1 to 6 is performed.
CN202210724127.2A 2022-06-23 2022-06-23 Parameter configuration method, device, electronic equipment and medium Pending CN117332934A (en)

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