Electricity meter outbound dispatching method, device, equipment and storage medium

Abstract

The present invention provides a method, device, equipment and storage medium for dispatching electric meter out of warehouse, wherein the method comprises: step 1, under the premise of satisfying the current basic strategy rules, randomly generating multiple electric meter out of warehouse schemes as the initial population, performing crossover and mutation of the initial population by genetic algorithm, and obtaining a new generation population; step 2, using the total out of warehouse time objective function and the task out of warehouse average time objective function to evaluate each individual in the new generation population, and taking the individual with the highest fitness and satisfying the constraint conditions as the selection scheme, if all individuals do not satisfy the constraint conditions, repeating step 1 to regenerate the new generation population until the selection scheme is obtained; step 3, executing the selection scheme to realize the diversion dispatching of electric meter out of warehouse. The present invention disassembles large-scale electric meter out of warehouse tasks through genetic algorithm, thereby improving the efficiency of electric meter out of warehouse dispatching.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity meter outbound delivery, and in particular to an electricity meter outbound delivery dispatching method, device, equipment and storage medium. Background Art

[0002] Electricity meters that have completed quality inspection need to be arranged for shipment. In actual application scenarios, there are many plans for electricity meter shipment, and it is necessary to find the plan with the highest execution efficiency.

[0003] In the related technology, the traditional method requires manual work to remove the meters that have completed the inspection from the warehouse, which is inefficient and prone to errors. When there are many tasks, some large tasks contain too many meters, which may cause small-scale tasks to wait in line for too long, resulting in waste of resources and inefficiency. In addition, the priority is not defined according to the actual situation of task execution, and the practicality is poor.

[0004] Based on the above analysis of the development status of this technical field, the existing technical solutions lack solutions that consider the overall and individual execution implementation of tasks and define task priorities. Summary of the invention

[0005] The object of the present invention is to provide a method, device, equipment and storage medium for dispatching electricity meters out of warehouse, aiming to solve the above-mentioned problems in the prior art.

[0006] According to a first aspect of an embodiment of the present invention, a method for dispatching electricity meters out of a warehouse is provided, comprising:

[0007] Step 1: Under the premise of satisfying the current basic strategy rules, randomly generate multiple meter dispatching plans as the initial population, perform crossover and mutation of the genetic algorithm on the initial population, and obtain a new generation population;

[0008] Step 2: Use the total outbound time objective function and the task outbound average time objective function to evaluate each individual in the new generation population, and select the individual with the highest fitness and that meets the constraints as the selection plan. If all individuals do not meet the constraints, repeat step 1 to regenerate the new generation population until a selection plan is obtained.

[0009] Step 3: Execute the selection plan to realize the diversion scheduling of the electricity meter out of the warehouse.

[0010] According to a second aspect of an embodiment of the present invention, there is provided an electric meter outbound dispatching device, comprising:

[0011] The population generation module is used to randomly generate multiple meter dispatching plans as the initial population under the premise of meeting the current basic strategy rules, and perform crossover and mutation of the genetic algorithm on the initial population to obtain a new generation of population;

[0012] The optimal selection module is used to evaluate each individual in the new generation population using the total outbound time objective function and the task outbound average time objective function, and select the individual with the highest fitness and satisfying the constraints as the selection scheme. If all individuals do not satisfy the constraints, the population generation module is repeatedly executed to regenerate the new generation population until a selection scheme is obtained.

[0013] The outbound dispatching module is used to execute the selection scheme to realize the diversion dispatching of the outbound electricity meters.

[0014] According to a third aspect of an embodiment of the present invention, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the electric meter outbound scheduling method provided in the first aspect of the present disclosure are implemented.

[0015] According to a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which a program for implementing information transmission is stored. When the program is executed by a processor, the steps of the meter dispatch scheduling method provided in the first aspect of the present disclosure are implemented.

[0016] The technical solution provided by the embodiment of the present invention includes the following beneficial effects: by disassembling large-scale meter outbound tasks through genetic algorithms, the overall operating time and individual operating time are shortened as much as possible, avoiding the situation where the queuing time of small tasks is too long, and improving the efficiency of meter outbound scheduling.

[0017] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0019] Figure 1 is a flow chart of a method for dispatching electric meters out of a warehouse according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of a delivery dispatch strategy framework according to an embodiment of the present invention;

[0021] Figure 3 It is a schematic diagram of a storage outbound task execution process record table according to an embodiment of the present invention;

[0022] Figure 4is a schematic diagram of an electric meter outbound dispatching device according to an embodiment of the present invention;

[0023] Figure 5 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0025] Method Embodiment

[0026] According to an embodiment of the present invention, a method for dispatching electricity meters out of storage is provided. Figure 1 is a flow chart of the method for dispatching electricity meters out of warehouse according to an embodiment of the present invention. Figure 1 As shown, the method for dispatching electricity meters out of the warehouse according to an embodiment of the present invention specifically includes:

[0027] In step S110, under the premise of satisfying the current basic strategy rules, a plurality of meter dispatching schemes are randomly generated as the initial population, and the initial population is subjected to crossover and mutation of the genetic algorithm to obtain a new generation population, specifically including:

[0028] The basic policy rules include outbound task priority configuration rules, line priority configuration rules and task priority configuration rules.

[0029] Among them, the outbound task priority configuration rule assigns different priorities to the meters belonging to different outbound tasks, and the first priority is assigned. The outbound tasks include calibration outbound, distribution outbound, transfer outbound, etc.

[0030] Among them, the line priority configuration rule is to match the execution line set that can realize the corresponding function according to the outbound task, determine the second priority of the allocation order according to the production attributes of the electric meter, and match the execution line corresponding to the processing level from the line set according to the second priority. The electric meter needs to be sent to the execution line to realize tasks such as calibration. The second priority is to respond to the execution order in the execution line.

[0031] Among them, the task priority configuration rule is to assign priority to the meters to be shipped out of the execution line according to the specific task type among the meters corresponding to the execution line, and it is the third priority. Taking calibration as an example, the specific task types of calibration and shipping tasks include random inspection and calibration tasks, full inspection and calibration tasks, inventory re-inspection and calibration tasks, etc.

[0032] That is to say, the outbound order is first formulated according to the type of outbound task based on actual needs, and the second priority is allocated within each outbound type based on the production attribute. In this embodiment, the production attribute is the production department corresponding to the electric meter. If the production department has the highest priority, the electric meters produced by this department have the highest second priority. The electric meters produced by this department are sent to the execution line with the highest level of processing, and finally the order is adjusted according to more detailed specific task types.

[0033] Under the premise of satisfying the outbound task priority configuration rules, line priority configuration rules and task priority configuration rules, the corresponding execution line and outbound order of each meter are generated to obtain a randomly assigned meter outbound plan, in which the same specific task type includes multiple meters to be outbound and the outbound order is random.

[0034] In the meter outbound plan corresponding to a certain outbound task, the specific task in which the number of meters is greater than the scale threshold is randomly divided into multiple subtasks, and the subtasks and the undivided specific tasks form a task set. The meter outbound strategies assigned to different calibration lines in the task set are randomly exchanged to achieve crossover, and the meter outbound plan is randomly changed to achieve mutation. However, the scope of mutation must be reasonable. Taking the calibration task as an example, in this embodiment, there are five execution lines that can execute the calibration task. Mutation can change the specific execution line corresponding to the task and the outbound order, but the selectable execution line must be the execution line used for calibration, that is, within the execution line set corresponding to the function. After crossover and mutation of the outbound plans of all outbound tasks in the initial population, a new generation of population is obtained.

[0035] In step S120, the total outbound time objective function and the task outbound average time objective function are used to evaluate each individual in the new generation population, and the individual with the highest fitness and satisfying the constraints is selected as the selection scheme. If all individuals do not satisfy the constraints, step 1 is repeated to regenerate the new generation population until a selection scheme is obtained, which specifically includes:

[0036] Simulate the total time after all the meters to be shipped out are completed, and use the total time as the result of the total shipping time objective function; simulate the average processing time of each shipping type, and use the average processing time as the result of the average shipping time objective function; add the total time and the average processing time to get the total evaluation value, and take the individual with the smallest total evaluation value as the selection plan.

[0037] The specific constraints include: the loading cycle, the outbound cycle, the maximum loading buffer size, the unloading cycle, the return cycle and the maximum unloading buffer size are within their respective threshold ranges.

[0038] Among them, the loading cycle refers to the average time to complete an electric meter from the exit of the calibration line to the calibration waiting area; the outbound cycle refers to the average time to complete an electric meter from the warehouse shelf to the exit of the calibration line; the maximum loading buffer refers to the maximum number of turnover boxes that can be stored in the loading buffer area of ​​the calibration line; the unloading cycle refers to the average time to complete an electric meter from the waiting unloading area to the entrance of the calibration line; the return cycle refers to the average time to complete an electric meter from the entrance of the calibration line to the warehouse shelf; the maximum unloading buffer refers to the maximum number of turnover boxes that can be stored in the unloading buffer area of ​​the calibration line.

[0039] In step S130, the selection scheme is executed to implement the diversion scheduling of the electricity meter out of the warehouse.

[0040] The above technical solutions of the embodiments of the present invention are illustrated with reference to the following drawings.

[0041] Figure 2 Schematic diagram of the outbound dispatching strategy framework of the embodiment of the present invention. Figure 2 As shown, the objective function, constraints, maintained inspection port queue and basic strategy are shown; Figure 3 Schematic diagram of the outbound task execution process record table of the embodiment of the present invention, such as Figure 3 As shown, a list of tasks that have been shipped out, are waiting to be shipped out, and are unassigned is displayed.

[0042] To sum up, in response to the existing problems, the meter outbound scheduling method invented this time uses a genetic algorithm to disassemble large-scale meter outbound tasks, so that the overall operating time and individual operating time are shortened as much as possible, avoiding the situation where the queuing time of small tasks is too long, and different outbound priorities are assigned according to the type of outbound task, and priorities are assigned to individual outbound tasks, so that the formulation of outbound strategies is more in line with actual needs, thereby improving the efficiency of meter outbound scheduling.

[0043] Device Embodiment

[0044] According to an embodiment of the present invention, a device for dispatching electricity meters out of warehouse is provided. Figure 4 is a schematic diagram of an electric meter outbound dispatching device according to an embodiment of the present invention. Figure 4 As shown, a meter outbound dispatching device according to an embodiment of the present invention specifically includes:

[0045] The population generation module 40 is used to randomly generate multiple meter dispatching plans as the initial population under the premise of satisfying the current basic strategy rules, and perform crossover and mutation of the initial population using a genetic algorithm to obtain a new generation population, specifically for:

[0046] Under the premise of meeting the outbound task priority configuration rules, line priority configuration rules and task priority configuration rules, the corresponding execution line and outbound order of each meter are generated to obtain a randomly assigned meter outbound plan, in which the same specific task type includes multiple meters to be outbound and the outbound order is random;

[0047] In the meter outbound plan corresponding to a certain outbound task, the specific task in which the number of meters is greater than the scale threshold is randomly divided into multiple subtasks, and the subtasks and the undivided specific tasks form a task set. The meter outbound strategies assigned to different calibration lines in the task set are randomly exchanged to achieve crossover, and the meter outbound plan is randomly changed to achieve mutation. After crossover and mutation of the outbound plans of all outbound tasks in the initial population, a new generation of population is obtained.

[0048] The optimal selection module 42 is used to evaluate each individual in the new generation population using the total outbound time objective function and the task outbound average time objective function, and take the individual with the highest fitness and satisfying the constraint conditions as the selection scheme. If all individuals do not satisfy the constraint conditions, the population generation module is repeatedly executed to regenerate the new generation population until a selection scheme is obtained;

[0049] The outbound dispatching module 44 is used to execute the selection scheme to realize the diversion dispatching of the outbound electricity meters.

[0050] To sum up, in response to the existing problems, the electric meter outbound dispatching device invented this time disassembles large-scale electric meter outbound tasks through genetic algorithms, so that the overall operating time and individual operating time are shortened as much as possible, avoiding the situation where the queuing time of small tasks is too long, and assigns different outbound priorities according to the type of outbound tasks, and assigns priorities to individual outbound tasks, so that the formulation of outbound strategies is more in line with actual needs, thereby improving the efficiency of electric meter outbound dispatching.

[0051] Electronic device embodiment

[0052] Figure 5 Schematic diagram of an electronic device according to an embodiment of the present invention. The electronic device 500 may include at least one processor 510 and a memory 520. The processor 510 may execute instructions stored in the memory 520. The processor 510 is connected to the memory 520 through a data bus. In addition to the memory 520, the processor 510 may also be connected to an input device 530, an output device 540, and a communication device 550 through a data bus.

[0053] The processor 510 may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0054] The memory 520 may be implemented by any type of volatile or nonvolatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0055] In the embodiment of the present disclosure, executable instructions are stored in the memory 520, and the processor 510 can read the executable instructions from the memory 520 and execute the instructions to implement all or part of the steps of any of the electricity meter dispatch scheduling methods in the above exemplary embodiments.

[0056] Computer Readable Storage Medium Embodiments

[0057] In addition to the above-mentioned methods and devices, the exemplary embodiments of the present disclosure may also be a computer program product or a computer-readable storage medium storing the computer program product, wherein the computer product includes computer program instructions, which can be executed by a processor to implement all or part of the steps described in any of the electricity meter dispatch scheduling methods in the above-mentioned exemplary embodiments.

[0058] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as "C" language or similar programming languages ​​and scripting languages ​​(e.g., Python). The program code may be executed entirely on the user computing device, partially on the user computing device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0059] Computer readable storage media can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of readable storage media include: a static random access memory (SRAM) with one or more wires electrically connected, an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk or an optical disk, or any suitable combination of the above.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dispatching electricity meters out of warehouse, characterized in that: include: Step 1: Under the premise of satisfying the current basic strategy rules, a plurality of electricity meter dispatching plans are randomly generated as an initial population, and the initial population is subjected to crossover and mutation of a genetic algorithm to obtain a new generation population; Among them, the basic strategy rules include outbound task priority configuration rules, line body priority configuration rules and task priority configuration rules; Among them, the outbound task priority configuration rule is to assign different priorities to the electric meters belonging to different outbound tasks, and it is the first priority; wherein, the line body priority configuration rule is to match the execution line body set that can realize the corresponding function according to the outbound task, determine the second priority of the allocation order according to the production attribute of the electric meter, and match the execution line body corresponding to the processing level from the line body set according to the second priority; wherein, the task priority configuration rule is to assign priorities to the electric meters to be outbound according to the specific task type in the electric meters corresponding to the execution line body, and it is the third priority; Step 2: Use the total outbound time objective function and the task outbound average time objective function to evaluate each individual in the new generation population, and use the individual with the highest fitness and satisfying the constraint conditions as the selection scheme. If all individuals do not satisfy the constraint conditions, repeat step 1 to regenerate the new generation population until a selection scheme is obtained. Step 3, executing the selection scheme to realize the diversion scheduling of the electricity meter out of the warehouse.

2. The method according to claim 1, characterized in that The method of randomly generating multiple electricity meter dispatching plans as the initial population under the premise of satisfying the current basic strategy rules specifically includes: Under the premise of satisfying the outbound task priority configuration rules, the line priority configuration rules and the task priority configuration rules, the corresponding execution line and outbound order of each meter are generated to obtain a randomly assigned meter outbound plan, wherein the same specific task type includes multiple meters to be outbound and the outbound order is random.

3. The method according to claim 2, characterized in that The performing of crossover and mutation of the initial population by genetic algorithm to obtain a new generation population specifically includes: In the meter outbound plan corresponding to a certain outbound task, a specific task in which the number of meters is greater than a scale threshold is randomly divided into multiple subtasks, and the subtasks and the undivided specific tasks form a task set. The meter outbound strategies assigned to different calibration lines in the task set are randomly exchanged to achieve crossover, and the meter outbound plan is randomly changed to achieve mutation. After crossover and mutation of the outbound plans of all outbound tasks in the initial population, a new generation population is obtained.

4. The method according to claim 1, characterized in that: The method of using the total outbound time objective function and the task outbound average time objective function to evaluate each individual in the new generation population and selecting the individual with the highest fitness and satisfying the constraint conditions specifically includes: Simulate the total time after all the electricity meters to be shipped out are completed, and use the total time as the result of the total shipping time objective function; simulate the average processing time of each shipping type, and use the average processing time as the result of the average shipping time objective function; add the total time and the average processing time to obtain the total evaluation value, and take the individual corresponding to the smallest total evaluation value as the selection plan.

5. The method according to claim 1, characterized in that The constraint conditions specifically include: the material loading cycle, the outbound cycle, the maximum amount of material loading buffer, the material unloading cycle, the return cycle and the maximum amount of material unloading buffer are within their respective threshold ranges.

6. An electric meter outbound dispatching device, characterized in that: include: A population generation module is used to randomly generate multiple electricity meter dispatching plans as initial populations under the premise of satisfying the current basic strategy rules, and to perform crossover and mutation of the initial populations using a genetic algorithm to obtain a new generation of populations; Among them, the basic strategy rules include outbound task priority configuration rules, line body priority configuration rules and task priority configuration rules; Among them, the outbound task priority configuration rule is to assign different priorities to the electric meters belonging to different outbound tasks, and it is the first priority; wherein, the line body priority configuration rule is to match the execution line body set that can realize the corresponding function according to the outbound task, determine the second priority of the allocation order according to the production attribute of the electric meter, and match the execution line body corresponding to the processing level from the line body set according to the second priority; wherein, the task priority configuration rule is to assign priorities to the electric meters to be outbound according to the specific task type in the electric meters corresponding to the execution line body, and it is the third priority; The optimal selection module is used to evaluate each individual in the new generation population using the total outbound time objective function and the task outbound average time objective function, and take the individual with the highest fitness and satisfying the constraint conditions as the selection scheme. If all individuals do not satisfy the constraint conditions, the population generation module is repeatedly executed to regenerate the new generation population until a selection scheme is obtained; The outbound dispatching module is used to execute the selection scheme to realize the diversion dispatching of the outbound electricity meters.

7. The device according to claim 6, characterized in that The population generation module is specifically used for: Under the premise of meeting the outbound task priority configuration rules, line priority configuration rules and task priority configuration rules, the corresponding execution line and outbound order of each meter are generated to obtain a randomly assigned meter outbound plan, in which the same specific task type includes multiple meters to be outbound and the outbound order is random; In the meter outbound plan corresponding to a certain outbound task, a specific task in which the number of meters is greater than a scale threshold is randomly divided into multiple subtasks, and the subtasks and the undivided specific tasks form a task set. The meter outbound strategies assigned to different calibration lines in the task set are randomly exchanged to achieve crossover, and the meter outbound plan is randomly changed to achieve mutation. After crossover and mutation of the outbound plans of all outbound tasks in the initial population, a new generation population is obtained.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the electricity meter dispatching method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an implementation program for information transmission, and when the program is executed by the processor, the steps of the meter dispatching method according to any one of claims 1 to 5 are implemented.

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