Goods picking and replenishment linkage decision-making method considering ergonomic risk and service platform

Abstract

The invention relates to a picking and replenishment linkage decision-making method considering human engineering risks and a service platform, and the method comprises the steps: obtaining polymer material list information and warehouse location information from a picking and replenishment data stream; coding according to the first to-be-supplemented goods quantity information corresponding to the polymer material list information, the polymer material list information and the storage location information, and generating a first double-coding population comprising first double-coding individuals; according to a non-dominated solution parameter and a target congestion degree corresponding to the first double-coding individual, performing a target selection operation corresponding to an NSGA-II algorithm on the first double-coding population to obtain a candidate double-coding individual; performing target genetic manipulation corresponding to the NSGA-II algorithm on all candidate double-coding individuals, and repeatedly executing target selection operation and target genetic manipulation on all candidate double-coding individuals generated after the target genetic manipulation is completed, the target double-coding population at least comprises the target double-coding individuals with the individual fitness smaller than the preset fitness threshold value.

Description

Technical Field

[0001] The present application relates to the field of intelligent manufacturing and smart logistics technology, and in particular to a picking and replenishment linkage decision-making method and service platform that takes ergonomic risks into consideration. Background Art

[0002] In the relevant technologies, large-scale customized production is adopted to meet the new business model of multi-variety and small-batch production. At the same time, in the relevant technologies, the vendor managed inventory model (VMI) and the kitting model are also adopted to solve the problems in customized production. That is, the material demand information is sent to the VMI warehouse, and the VMI warehouse is responsible for transporting the materials to the production workshop. The workshop workers then replenish the materials to the shelves in the picking area. The picking workers then pick all the parts needed to assemble a product into a material box, and complete the delivery of materials in the form of material boxes, thereby reducing the assembly workers' material collection time and error rate.

[0003] In the related art, technical solutions for picking and replenishment based on the VMI model usually focus on solving a single problem. However, in the mass customized production model, their effectiveness is limited because the problems of picking and replenishment are handled sequentially or in isolation without extending the analysis to include the collaborative optimization of picking and replenishment operations. At the same time, in the related art, existing technical solutions for picking and replenishment focus on the systematization of operations, which leads to suboptimal resource utilization and increases ergonomic risks for employees, affecting their work efficiency and physical and mental burden.

[0004] At present, there is no effective solution to the problems of picking-replenishment collaborative decision-making in large-scale customized production workshops, which may easily lead to insufficient adaptability of dynamic customized orders, complex picking-replenishment operations under customized requirements, and increased ergonomic risks. Summary of the invention

[0005] The embodiments of the present application provide a method and service platform for linkage decision-making of picking and replenishment taking into account ergonomic risks, so as to at least solve the problems of insufficient adaptability to dynamic customized orders, complex picking and replenishment operations under customized requirements, and increased ergonomic risks easily caused by related technologies for linkage decision-making of picking and replenishment in large-scale customized production workshops.

[0006] In a first aspect, an embodiment of the present application provides a method for decision-making in linkage between picking and replenishment considering ergonomic risks, comprising: after obtaining aggregated material list information and storage location information corresponding to a target set picking area from an acquired replenishment picking data stream, determining first material quantity information to be replenished corresponding to a current wave order according to the aggregated material list information, and performing replenishment picking linkage encoding on the first material information to be replenished, the aggregated material list information and the storage location information to generate a first double-coded population, wherein the first double-coded population includes a plurality of first double-coded individuals; performing a target selection operation corresponding to a preset NSGA-Ⅱ algorithm on the first double-coded population according to a non-dominated solution parameter and a target congestion degree corresponding to the first double-coded individual to obtain a candidate double-coded individual, wherein the non-dominated solution parameter is based on the individual fitness corresponding to the first double-coded individual, The target congestion degree is calculated by the total operation time of replenishment picking and the ergonomic risk score of picking corresponding to the first dual-coded individual in the same non-dominated layer; the target genetic operation corresponding to the NSGA-Ⅱ algorithm is performed on all the candidate dual-coded individuals, and the target selection operation and the target genetic operation are repeatedly performed on all the candidate dual-coded individuals generated after completing the target genetic operation, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation.

[0007] In a second aspect, an embodiment of the present application provides a service platform including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the picking and replenishment linkage decision-making method considering ergonomic risks as described in the first aspect are implemented.

[0008] In a third aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the picking and replenishment linkage decision-making method considering ergonomic risks as described in the first aspect above.

[0009] Compared with the related art, the picking and replenishment linkage decision method, device, service platform and storage medium provided in the embodiment of the present application consider ergonomic risks. After obtaining the aggregated material list information and the storage location information corresponding to the target set picking area from the acquired replenishment picking data stream, the first material quantity information to be replenished corresponding to the current wave order is determined according to the aggregated material list information, and the first material information to be replenished, the aggregated material list information and the storage location information are coded for replenishment picking linkage to generate a first double-coded population, wherein the first double-coded population includes multiple first double-coded individuals; according to the non-dominated solution parameters and target congestion corresponding to the first double-coded individuals, the first double-coded population is subjected to a target selection operation corresponding to a preset NSGA-Ⅱ algorithm to obtain candidate double-coded individuals, wherein the non-dominated solution parameters are generated by non-dominated sorting based on the individual fitness corresponding to the first double-coded individuals, and the individual fitness includes parameters of the following two dimensions: total replenishment picking operation time and picking ergonomic risk score, The target congestion is calculated by jointly calculating the total replenishment picking operation time and the picking ergonomic risk score corresponding to the first dual-coded individuals in the same non-dominated layer; performing a target genetic operation corresponding to the NSGA-Ⅱ algorithm on all the candidate dual-coded individuals, and repeating the target selection operation and the target genetic operation on all the candidate dual-coded individuals generated after completing the target genetic operation, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation, which solves the problems of insufficient adaptability of dynamic customized orders, complex picking-replenishment operations under customized requirements, and increased ergonomic risks in the picking-replenishment linkage decision of large-scale customized production workshops in the related technology, so as to achieve high-efficiency and low ergonomic risk material delivery, promote agile operation of production workshops and improve production efficiency.

[0010] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 It is a hardware structure block diagram of a terminal of the method for decision-making in linkage between picking and replenishment considering ergonomic risks according to an embodiment of the present application; Figure 2 is a flow chart of a method for decision-making in linkage between picking and replenishment considering ergonomic risks according to an embodiment of the present application; Figure 3 It is a structural block diagram of a picking and replenishment linkage decision-making device that takes ergonomic risks into consideration according to an embodiment of the present application. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by a person of ordinary skill in the art without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for a person of ordinary skill in the art related to the contents disclosed in the present application, some changes such as design, manufacture or production based on the technical contents disclosed in the present application are only conventional technical means, and should not be understood as insufficient contents disclosed in the present application.

[0013] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by a person of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0014] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation and may represent the singular or plural. The terms "including", "comprising", "having" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include unlisted steps or units, or may also include other steps or units inherent to these processes, methods, products or devices. The "multiple links" involved in this application refer to links greater than or equal to two. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" may represent: A exists alone, A and B exist at the same time, and B exists alone. The terms "first", "second", "third" and the like involved in this application are only used to distinguish similar objects and do not represent a specific ordering of objects.

[0015] Before describing the embodiments of the present application, the relevant terms involved in the embodiments of the present application are described as follows: Manufacturing system: refers to the collection of various workstations and related processes used to assemble products.

[0016] Vendor managed inventory: refers to an inventory management method in which the upstream enterprise in the supply chain actively manages and controls the inventory of downstream enterprises based on the demand plan, sales information and inventory level of downstream enterprises in accordance with the agreement reached by both parties.

[0017] Bill of Materials: A list of all subassemblies, intermediate parts, parts, and raw materials that make up the parent assembly, including the quantity of each sub-item required for assembly.

[0018] Inventory Management Unit: refers to the unique identifier for different products or commodities in inventory management.

[0019] Ergonomics: refers to the science that studies the relationship between the three major elements of man, machine and environment in the "man-machine-environment" system, and provides theories and methods for solving the efficiency and health problems of people in the system.

[0020] Ergonomic risks: refers to factors in the working environment that may cause harm to human health and safety.

[0021] Complete set picking: refers to obtaining material requirements based on order information and product BOM, and picking materials in quantities that just meet product production needs.

[0022] Mass customization: refers to a production method that provides customized products and services based on customers' personalized needs with low cost, high quality and efficiency of large-scale production.

[0023] Production-logistics linkage: refers to the seamless connection and efficient collaboration between production activities and logistics activities.

[0024] The embodiments of the present application are described below with reference to the accompanying drawings:

[0025] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. Taking running on a terminal as an example, Figure 1 1 is a hardware structure block diagram of a terminal of a method for decision-making in linkage between picking and replenishment considering ergonomic risks according to an embodiment of the present application. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the terminal may also include a transmission device 106 and an input / output device 108 for communication functions. A person skilled in the art can understand that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0026] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the picking and replenishment linkage decision method considering ergonomic risks in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0027] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by the communication provider of the terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0028] This embodiment provides a method for decision-making in linkage between picking and replenishment taking into account ergonomic risks, which is run on the above-mentioned terminal. Figure 2 is a flow chart of a method for decision-making in linkage between picking and replenishment considering ergonomic risks according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0029] Step S201, after obtaining the aggregate material list information and the storage location information corresponding to the target set picking area from the acquired replenishment picking data stream, determine the first material quantity information to be replenished corresponding to the current wave order according to the aggregate material list information, and perform replenishment picking linkage coding on the first material information to be replenished, the aggregate material list information and the storage location information to generate a first double-coded population, wherein the first double-coded population includes multiple first double-coded individuals.

[0030] In this embodiment, the execution subject of the picking and replenishment linkage decision of the embodiment of the present application is the associated preset Vendor Managed Inventory (VMI) system, and the replenishment picking data stream is obtained from the VMI system; after receiving several customer orders, the VMI system will interpret each customer order to determine the corresponding customer order material list, and then reprocess the customer order material list to generate a plurality of aggregate material lists. At the same time, the VMI system also stores the storage location information corresponding to the target set picking area (that is, the corresponding shelf and the shelf location information set on the shelf); in this embodiment, after obtaining the replenishment picking data stream, the replenishment picking data stream will be interpreted to obtain the replenishment material quantity of large-scale customized production corresponding to the current linkage decision to meet the production demand of the current wave; in this embodiment, the replenishment decision to replenish the goods to the corresponding location of the target set picking area will be made according to the replenishment material quantity, that is, the corresponding replenishment material quantity (all materials required to meet the production of the current wave order) will be transported to the target set picking area, and then, based on The picking decision is made based on the replenishment decision information placed in the target complete picking area, that is, all materials contained in the target product that meets the production needs of the customer order are picked accordingly, that is, the picking decision information of the picking order in which the decision picking object starts from the picking platform, walks to the corresponding storage location to pick, and then returns to the picking platform. One picking decision information corresponds to the arrangement of the picking order of materials contained in one target product, and also corresponds to a picking path for picking multiple materials. In this embodiment, the decision result of the linkage decision of picking and replenishment includes replenishment decision information and picking decision information, and in the decision iteration process, the replenishment decision information is first generated, and then the picking decision information is decided based on the generated replenishment decision information. By continuously optimizing the linkage decision in the decision iteration process, the replenishment decision information that achieves the preset target (the best in terms of non-dominated sorting and congestion, and the non-dominated sorting and congestion are both determined by the total operation time of replenishment picking and the ergonomic risk score) is generated.

[0031] In this embodiment, each first double-coded individual includes a replenishment code individual with multiple storage location allocation codes and a picking code individual with multiple picking sub-codes, wherein a storage location allocation code is used to represent the replenishment storage location information allocated to a material, and the position of a storage location allocation code in the replenishment code individual indicates the material number of the corresponding material, that is, it indicates which material. For example, the material numbers corresponding to the materials to be replenished are set as: 1, 2, 3, 4. During replenishment, material 1 is allocated to storage location 10, material 2 is allocated to storage location 5, material 3 is allocated to storage location 18, and material 4 is allocated to storage location 3. Then the corresponding replenishment code individual is

[10] [5]

[18] [3]; a picking sub-code The code body is used to represent the picking decision information for picking multiple materials corresponding to a target product. The position of a picking sub-code body in the picking code individual indicates the model or product type of the target product corresponding to the picking sub-code body. For example, the second picking sub-code body in the picking code individual corresponds to the picking sub-code body corresponding to the second target product. A picking sub-code body includes multiple picking codes. A picking code of the picking sub-code body corresponds to a cargo location allocation code corresponding to a material to be picked. The order of the picking codes in the picking sub-code body represents the order in which the corresponding materials are picked. The picking codes are arranged in the order of the cargo locations that the picking objects need to visit when completing the picking of a target product. In this embodiment, the picking station and the shelf are coded with non-repeating natural numbers. Since the picking object starts from the picking station and returns to the picking station after picking, the picking codes corresponding to the picking station are 0 and J+1, where J represents the type of material corresponding to a target product. The picking codes corresponding to the shelf are 1 to J. The gene length of a picking code individual is set to be equal to the number of target products required in the order corresponding to the aggregated picking material list information × (the types of different materials required for a target product + 2). For example, the picking order for multiple materials of target product 1 is set to: shelf 5, shelf 18, shelf 7, shelf 10, then a picking sub-code body is set to [0][5]

[18] [7]

[10] [2 5][0]. In this embodiment, during the encoding process, the picking code individual is assigned a code to the cargo location numbered 0 between two adjacent picking sub-coding bodies (corresponding to returning to the picking platform), and a cargo location assignment code is omitted at the end of the previous picking sub-coding body. For example, the picking order of multiple materials of target product 2 is set to: cargo location 8, cargo location 7, cargo location 16, cargo location 25, and the picking sub-coding body corresponding to target product 2 is set to [0][8][7]

[16]

[25] [0]. Then the picking code individual consisting of target product 1 and target product 2 is [0][5]

[18] [7]

[10]

[25] [0][8][7]

[16]

[25] .

[0032] Step S202: According to the non-dominated solution parameters and target congestion corresponding to the first dual-coded individual, the target selection operation corresponding to the preset NSGA-Ⅱ algorithm is performed on the first dual-coded population to obtain candidate dual-coded individuals, wherein the non-dominated solution parameters are generated by non-dominated sorting based on the individual fitness corresponding to the first dual-coded individual, and the individual fitness includes parameters of the following two dimensions: total operation time for replenishment picking and ergonomic risk score for picking; the target congestion is calculated jointly based on the total operation time for replenishment picking and ergonomic risk score for picking corresponding to the first dual-coded individual in the same non-dominated layer.

[0033] In this embodiment, after the generation of the initial population (corresponding to the first dual-coded population) is completed, the individual fitness of each first dual-coded individual in the initial population is calculated in two dimensions. In this embodiment, the individual fitness of the two dimensions corresponding to the first dual-coded individual includes the total operation time for replenishment and the ergonomic risk score of picking; in this embodiment, after determining the individual fitness corresponding to each first dual-coded individual, based on the total replenishment and picking time and the ergonomic risk score of picking in the individual fitness, the first dual-coded population is sorted by non-dominated solutions to obtain the corresponding non-dominated solution parameters; it can be understood that the sorting of non-dominated solutions corresponding to the NSGA-Ⅱ algorithm performed in this embodiment is known and clear to those skilled in the art, and does not constitute an unclear limitation to the present application; at the same time, in this embodiment, after calculating the individual fitness of the two dimensions corresponding to each individual, the crowding distance of each individual under the non-dominated solution is calculated, and the difference in the total replenishment and picking time and the difference in the ergonomic risk score of picking between individuals in the same non-dominated layer are calculated respectively, and then the difference in the individual fitness of the two dimensions is accumulated to obtain the target crowding degree corresponding to each individual.

[0034] In this embodiment, a preset number of first dual-coded individuals are randomly selected from the first dual-coded population, and then the optimal individual is selected (target selection operation is performed) based on a comparison between the non-dominated solution parameter and the target crowding degree, that is, a preset number of candidate dual-coded individuals are obtained.

[0035] Step S203, performing the target genetic operation corresponding to the NSGA-Ⅱ algorithm on all candidate dual-coded individuals, and repeating the target selection operation and the target genetic operation on all candidate dual-coded individuals generated after completing the target genetic operation, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation.

[0036] In this embodiment, after all candidate dual-coded individuals are obtained, a crossover operation and a mutation operation corresponding to the NSGA-Ⅱ algorithm are performed to complete a genetic operation. After that, a target selection operation based on the non-dominated solution parameters and the target congestion of the corresponding individual and a corresponding target genetic operation are performed to generate the corresponding dual-coded individuals. Then, after a preset number of iterations or the individual fitness corresponding to each dual-coded individual converges, a target dual-coded population including the target dual-coded individual is obtained. After the target dual-coded population is obtained, the dual-coded individual with the best individual fitness is selected from the target dual-coded population to obtain the corresponding target dual-coded individual. Then, the replenishment decision information and the picking decision information are interpreted from the target dual-coded individual to generate the corresponding decision result.

[0037] Through the above steps S201 to S203, after obtaining the aggregated material list information and the storage location information corresponding to the target set picking area from the acquired replenishment picking data stream, the first material quantity information to be replenished corresponding to the current wave order is determined according to the aggregated material list information, and the first material information to be replenished, the aggregated material list information and the storage location information are coded for replenishment picking linkage to generate a first double-coded population, wherein the first double-coded population includes a plurality of first double-coded individuals; according to the non-dominated solution parameters and target congestion corresponding to the first double-coded individuals, the first double-coded population is subjected to a target selection operation corresponding to the preset NSGA-Ⅱ algorithm to obtain candidate double-coded individuals, wherein the non-dominated solution parameters are generated by non-dominated sorting based on the individual fitness corresponding to the first double-coded individuals, and the individual fitness includes parameters of the following two dimensions: total replenishment picking operation time and picking ergonomic risk score, and the target congestion is obtained by selecting the candidate double-coded individuals according to the non-dominated solution parameters and the target congestion corresponding to the first double-coded individuals. The total operation time of replenishment picking and the ergonomic risk score of picking corresponding to the first dual-coded individual in the dominant layer are calculated together; the target genetic operation corresponding to the NSGA-Ⅱ algorithm is performed on all candidate dual-coded individuals, and the target selection operation and the target genetic operation are repeatedly performed on all candidate dual-coded individuals generated after the target genetic operation is completed, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation, which solves the problems of insufficient adaptability of dynamic customized orders, complex picking-replenishment operations under customized requirements, and increased ergonomic risks in the related technology for the picking-replenishment linkage decision of large-scale customized production workshops, so as to achieve high-efficiency and low ergonomic risk material delivery, promote agile operation of production workshops and improve production efficiency.

[0038] It should be noted that the embodiments of the present application break through the bottlenecks of low adaptability to dynamic customized orders under the large-scale customized production model, complex picking-replenishment operations under customized needs, and increased ergonomic risks. In a manufacturing environment where the operation process is transparent and traceable, starting from the underlying interactive logic and overall operation mechanism of picking-replenishment, the balance between ergonomic risks and operational efficiency is considered, and a linkage decision-making method is proposed to achieve high-efficiency, low-ergonomic-risk material delivery and promote the agile operation and development of production workshops.

[0039] In some embodiments, the first to-be-replenished material information, the aggregated material list information, and the storage location information are coded for replenishment and picking linkage to generate a first double-coded population, which is achieved by the following steps:

[0040] Step 21, obtaining multiple target materials corresponding to the first material information to be replenished, and determining the storage codes of all storage locations according to the storage location information.

[0041] Step 22, based on the golden storage location allocation strategy, multiple target materials and storage codes are integer-encoded to generate storage location allocation codes corresponding to the replenishment storage location information allocated to each target material.

[0042] Step 23, determining the multiple picking materials corresponding to the target product associated with the aggregate material list, selecting the storage location allocation codes corresponding to the multiple picking materials corresponding to each target product according to the picking order divided by the codes from all the storage location allocation codes, and performing integer encoding on all the selected storage location allocation codes to obtain a picking sub-code body corresponding to a target product, wherein the order of the storage location allocation codes in the corresponding picking sub-code body represents the order in which the corresponding picking materials are picked, and the picking sub-code body is also used to represent the picking decision information for picking the multiple picking materials corresponding to a target product;

[0043] Step 24, after encoding all the cargo location allocation codes and generating replenishment code individuals, encode all the picking sub-code entities to generate picking code individuals, encode the replenishment code individuals and the picking code individuals into the first double-coded individuals, and initialize the population of the first double-coded individuals to generate the first double-coded population.

[0044] In this embodiment, each element in the replenishment code individual corresponds to a material code, and the value of a storage location allocation code indicates the storage location number to which the material is assigned. A storage location allocation code is used to represent the replenishment location information assigned to a material. The position of a storage location allocation code in the replenishment code individual indicates the material number of the corresponding material, that is, which material it indicates. For example, the material numbers corresponding to the materials to be replenished are set to: 1, 2, 3, 4. During replenishment, material 1 is assigned to storage location 10, material 2 is assigned to storage location 5, material 3 is assigned to storage location 18, and material 4 is assigned to storage location 3. The corresponding replenishment code individual is

[10] [5]

[18] [3].

[0045] In this embodiment, we start from the entrance of the shelf. Assuming there are S shelves, the shelves are divided into M rows and N layers. The cargo locations are numbered in the order of shelf, row, and layer to generate the following cargo location number table 1: Table 1

[0046] In this embodiment, after the cargo location is numbered, the material number and the cargo location number are matched one by one, so as to generate the corresponding cargo location allocation code and replenishment code individual; at the same time, when processing the cargo location allocation, an adjustment mechanism is set to check and adjust the repeated or out-of-bounds cargo location numbers to ensure that all allocated cargo location numbers are unique and within the valid range, that is, each material is finally allocated to a valid, unoccupied cargo location.

[0047] In this embodiment, a picking code of the picking sub-code body of the picking code individual represents a cargo location number. The cargo location numbers are arranged in the order of the cargo locations that the picking object needs to visit when completing the picking of all materials of a target product, and a picking sub-code body is generated accordingly. When arranging the order of the picked cargo locations, the picking station and the cargo locations are coded as non-repeating natural numbers. Because the picking object starts from the picking station and returns to the picking station after picking, the picking codes corresponding to the picking station are 0 and J+1, J represents the type of material corresponding to a target product, and the picking codes corresponding to the cargo locations are 1 to J. The gene length of a picking code individual is set to be equal to the number of target products required in the order corresponding to the aggregated picking material list information × (the types of different materials required for a target product + 2). For example: the picking order for multiple materials of target product 1 is set to: cargo location Position 5, position 18, position 7, and position 10, then a picking sub-coding body is set to [0][5]

[18] [7]

[10]

[25] [0]. In this embodiment, during the encoding process, the picking coding individual is assigned a code to the cargo position numbered 0 between two adjacent picking sub-coding bodies (corresponding to returning to the picking station), and a cargo position assignment code is omitted at the end of the previous picking sub-coding body. For example: the picking order of multiple materials of target product 2 is set to: cargo position 8, cargo position 7, cargo position 16, and cargo position 25, and the picking sub-coding body corresponding to target product 2 is set to [0][8][7]

[16]

[25] [0], then the picking coding individual consisting of target product 1 and target product 2 is [0][5]

[18] [7]

[10]

[25] [0][8][7]

[16]

[25] .

[0048] Through the above steps 21 to 24, the replenishment and picking linkage coding is realized according to the first material information to be replenished, the aggregate material list information and the storage location information, and the initial coding population is generated to provide a data basis for subsequent population iterations. At the same time, through coding and population initialization, the material information to be replenished and the storage location information of the complete picking area are associated, providing data for the generation of replenishment decision information and picking decision information.

[0049] It should be noted that, in this embodiment, each first double-coded individual includes a storage location allocation and picking order decision plan, and the decision plan is generated based on the golden storage location allocation strategy, which prioritizes placing materials with high demand frequency in easily accessible locations to reduce picking time and improve efficiency.

[0050] In some embodiments, the iteration of the population is performed by:

[0051] Step 31, determining the second dual-coded individual of the current decision iteration, wherein the second dual-coded individual includes one of the following: the first dual-coded individual, and the candidate dual-coded individual generated after completing the target genetic operation corresponding to the previous decision iteration.

[0052] In this embodiment, when the second dual-coded individual is the first dual-coded individual, it means that the genetic evolution processing based on the NSGA-Ⅱ algorithm is performed based on the initial dual-coded population; when the second dual-coded individual is an alternative dual-coded individual, it means that the genetic evolution processing based on the NSGA-Ⅱ algorithm is performed based on the non-initial dual-coded population.

[0053] Step 32: determine the non-dominated layer corresponding to the second dual-coded individual according to the non-dominated solution parameter corresponding to each second dual-coded individual, and determine the target congestion degree corresponding to each second dual-coded individual in the same non-dominated layer.

[0054] In this embodiment, the second dual-coded population is divided into different non-dominated layers according to the fitness values ​​of individual fitness (including total replenishment operation time and picking ergonomic risk score), and the first-layer individuals are removed from the second dual-coded population. If the remaining individuals are not empty, the level allocation is repeated for the remaining individuals and the individual level and domination counter are updated. Then, the first-layer individuals are continued to be removed from the population, and the cycle ends until the remaining individuals are empty, and the non-dominated frontiers of each layer are output.

[0055] In this embodiment, the crowding distance is calculated for each second dual-coded individual in the non-dominated layer, and the difference between the second dual-coded individual and its adjacent individuals is calculated based on one of the total replenishment operation time and the picking ergonomic risk score. Then, the differences in the two dimensions of the total replenishment operation time and the picking ergonomic risk score are accumulated (normalization is used in the accumulation process) to obtain the total crowding degree corresponding to each second dual-coded individual, that is, the target crowding degree. It can be understood that the target crowding degree reflects the distribution uniformity of the solution (a second dual-coded individual). The higher the crowding degree, the sparser the solution is, which is conducive to maintaining the diversity of the population and ensuring the uniform distribution of the Pareto front.

[0056] Step 33, based on the non-dominated layer and target congestion of the second dual-coded individuals, a tournament selection method is used to select a preset number of second dual-coded individuals from multiple second dual-coded individuals one by one to obtain multiple third dual-coded individuals, wherein the third dual-coded individuals include one of the following: candidate dual-coded individuals, and alternative dual-coded individuals generated after completing the current decision iteration.

[0057] In this embodiment, a tournament selection method is adopted to randomly select N second dual-coded individuals, and compare them according to their non-dominated layers and crowding distances to select the best N individuals; in this embodiment, a binary tournament selection method is adopted to take out two corresponding individuals from the second dual-coded population, and give priority to comparing the non-dominated layers to which the two corresponding individuals belong, and take the one ranked higher. When the rankings of the non-dominated layers are consistent, the target crowding degrees are compared again, and the one with the larger target crowding degree is taken. This is repeated N times to obtain the N best individuals.

[0058] Through the above steps 31 to 33, the selection operation is performed on the population of the current iteration, thereby realizing the selection of the best individual.

[0059] In some embodiments, based on the non-dominated layer and target congestion of the second dual-coded individuals, a tournament selection method is used to select a preset number of second dual-coded individuals one by one from a plurality of second dual-coded individuals, which is implemented by the following steps:

[0060] Step 41, using the tournament selection method, randomly select two second dual-coded individuals from multiple second dual-coded individuals to obtain intended dual-coded individuals, and determine whether the two intended dual-coded individuals are in the same non-dominated layer.

[0061] Step 42, when it is determined that the two intended dual-coded individuals are in the same non-dominated layer, the intended dual-coded individual with the largest target congestion is used as the corresponding third dual-coded individual; and when it is determined that the two intended dual-coded individuals are not in the same non-dominated layer, the intended dual-coded individual with a higher non-dominated layer is used as the corresponding third dual-coded individual.

[0062] Step 43, repeatedly executing the operations of selecting two intended dual-coded individuals using the tournament selection method and selecting a corresponding third dual-coded individual from the two corresponding intended dual-coded individuals, until a preset number of third dual-coded individuals are obtained.

[0063] Through the above steps 41 to 43, the selection of individuals based on the tournament selection method is realized, providing data for performing the target genetic operation corresponding to the NSGA-Ⅱ algorithm and solving the optimal solution.

[0064] In some of the embodiments, after obtaining a plurality of third double-coded individuals, the following steps are further performed:

[0065] In step 51, two third double-coded individuals randomly obtained from multiple third double-coded individuals are used as the parent double-coded individuals currently being processed, and the replenishment coded individuals and picking coded individuals corresponding to the two parent double-coded individuals are obtained to obtain two candidate parent replenishment coded individuals and two candidate parent picking coded individuals.

[0066] Step 52, divide all the cargo location allocation codes corresponding to the candidate parent replenishment code individuals into a first cross cargo location code group and a first mapping cargo location code group, and combine the first mapping cargo location code group of a corresponding candidate parent replenishment code individual with the first cross cargo location code group of another corresponding candidate parent replenishment code individual to generate two candidate child replenishment code individuals, and randomly mutate all the cargo location allocation codes of the candidate child replenishment code individuals to generate new child replenishment code individuals.

[0067] Step 53, after selecting the picking sub-coding bodies corresponding to multiple target products from all the picking sub-coding bodies of the two candidate parent picking coding individuals, divide all the storage location allocation codes of the two picking sub-coding bodies corresponding to each target product into a second cross storage location code group and a second mapping storage location code group, and combine the second mapping storage location code group corresponding to one of the two picking sub-coding bodies with the second cross storage location code group corresponding to the other picking sub-coding body to generate two new picking sub-coding bodies corresponding to the corresponding target products, and combine all the new picking sub-coding bodies corresponding to the candidate parent picking coding individuals with the picking sub-coding bodies that have not been selected to generate new child picking coding individuals corresponding to the corresponding candidate parent picking coding individuals.

[0068] In this embodiment, a partially mapped crossover (PMX) operator is used to perform a crossover operation on the candidate parent replenishment coding individual and the candidate parent picking coding individual of each parent dual-coding individual. It can be understood that the partial mapping method using the PMX operator is to exchange some genes of the two parent individuals to the offspring, construct a mapping relationship of the exchanged genes, replace the offspring code according to the mapping relationship, and maintain the relative order between the genes.

[0069] In this embodiment, a partial mapping crossover operation is performed on the candidate parent replenishment code individuals of the parent double-coded individuals, and random mutation is used to randomly mutate all the cargo location allocation codes of the candidate child replenishment code individuals, that is, a certain cargo location allocation code of the candidate parent replenishment code individuals is randomly changed with a certain probability for mutation, for example: a replenishment code individual coded as

[10] [5]

[18] [3] is randomly mutated to generate a replenishment code individual of

[10]

[25]

[18] [3]; it should be noted that the random mutation operator obeys the boundary constraints. During the mutation process, any new cargo location number is generated by random selection within the valid range, ensuring that the newly allocated cargo location number does not exceed the preset cargo location range. In addition, if the newly generated cargo location number is occupied, it is necessary to find an unoccupied valid cargo location number to replace it, so as to ensure the feasibility of the replenishment decision.

[0070] Step 54, after the new offspring replenishment coded individuals and the corresponding new offspring picking coded individuals are combined into the new offspring double coded individuals corresponding to the third double coded individuals, all the new offspring double coded individuals and all the third double coded individuals are merged into a candidate double coded population, and based on the non-dominated layer and target congestion of all fourth double coded individuals corresponding to the candidate double coded population, a preset number of fourth double coded individuals are selected one by one using the tournament selection method to obtain a new double coded population corresponding to the current decision iteration, and the double coded individuals of the new double coded population are used as the double coded individuals generated after completing the current decision iteration.

[0071] In this embodiment, after performing selection operations, crossover and mutation operations on the population to generate new offspring individuals, the parent generation dual-coded individuals and the new offspring are merged to form a corresponding population, and then from the merged population (the number of corresponding individuals is twice the number of the set population), the non-dominated layer and target crowding degree of each individual are used to perform tournament selection, thereby obtaining the next generation population that matches the number of individuals in the set population, that is, obtaining a new dual-coded population.

[0072] Through the above steps 51 to 54, genetic selection, genetic crossover and genetic variation operations are implemented on the dual-coding population in each iteration, and the next generation population is generated.

[0073] In some of the embodiments, before determining the non-dominated layer corresponding to the second dual-coded individual according to the non-dominated solution parameter corresponding to each second dual-coded individual, the following steps are further performed:

[0074] Step 61, obtaining the total replenishment picking operation time and picking ergonomic risk score corresponding to the second double-coded individual.

[0075] In this embodiment, the picking ergonomic risk score is determined by evaluating and scoring the working posture using a preset ergonomic risk assessment method, such as the Rapid Entire Body Assessment (REBA) method.

[0076] Step 62, respectively calculate the first difference of the total replenishment picking operation time corresponding to any two second dual-coded individuals and the second difference corresponding to the picking ergonomic risk score, and respectively determine whether the first difference and the second difference are less than a preset threshold.

[0077] Step 63: when it is determined that one of the first difference and the second difference is less than a preset threshold, the two second dual-coded individuals are determined to be in the same non-dominated layer, and the corresponding non-dominated layer is recorded as the non-dominated solution parameter corresponding to the two second dual-coded individuals.

[0078] Through the above steps 61 to 63, the non-dominated solution parameters of the dual-coded individuals of the current iteration are determined, that is, the non-dominated solutions of the individuals in the dual-coded population of the current iteration are sorted, thereby achieving stratification.

[0079] In some embodiments, determining the target crowding degree corresponding to each second dual-coded individual in the same non-dominated layer is achieved by the following steps:

[0080] Step 71 : Select two second dual-coded individuals adjacent to the corresponding second dual-coded individual from all second dual-coded individuals in the same non-dominated layer to obtain a fifth dual-coded individual and a sixth dual-coded individual.

[0081] Step 72, according to the ratio of the third difference of the total replenishment picking operation time corresponding to the fifth dual-coded individual and the sixth dual-coded individual to the first target time difference, determine the operation time congestion distance corresponding to the corresponding second dual-coded individual, and according to the ratio of the fourth difference of the picking ergonomic risk score corresponding to the fifth dual-coded individual and the sixth dual-coded individual to the first target coefficient difference, determine the ergonomic risk congestion distance corresponding to the corresponding second dual-coded individual, wherein the first target time difference is the difference between the maximum and minimum values ​​of the total replenishment picking operation time corresponding to all second dual-coded individuals in the same non-dominated layer, and the first target coefficient difference is the difference between the maximum and minimum values ​​of the picking ergonomic risk scores corresponding to all second dual-coded individuals in the same non-dominated layer.

[0082] In this embodiment, the third difference or the fourth difference is calculated using the following formula: represents the crowding distance corresponding to the i-th double-coded individual in the operation time crowding distance or ergonomic risk crowding distance, represents the crowding distance of the mth operation time or the crowding distance of ergonomic risk, represents the maximum value of the crowding distance or ergonomic risk crowding distance at the mth operation time among all double-coded individuals, It represents the minimum value of crowding distance or ergonomic risk crowding distance at the mth operation time among all dual-coded individuals.

[0083] Step 73, taking the sum of the operation time crowding distance and the ergonomic risk crowding distance as the target crowding degree corresponding to the corresponding second dual-coded individual.

[0084] In some of the embodiments, after determining the second dual-coded individual of the current decision iteration, the method includes: Calculate the corresponding total replenishment picking time PRTT according to the following formula:

[0085] The picking ergonomic risk score PERT is calculated as follows: Calculate the total replenishment picking time PRTT and the picking ergonomic risk score PERT, satisfying the following constraints: ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;

[0086] Among them, the target material set is I, I={1,2,…,i,…,|I|}, i represents the i-th target material; the order set corresponding to the aggregate material list is O, O={1,2,…,o,…,|O|}, o represents the o-th aggregate material list; the set of arrival waves of replenishment materials is W, W={1,2,…,w,…,|W|}, w represents the w-th wave; the replenishment object set is R, R={1,2,…,r,…,|R|}, r represents the r-th replenishment object; the picking object set is B, B={1,2,…,b,…,|B|}, b represents the b-th picking object; the storage location set is J, J={1,2,…,j,…,|J|}, j represents the j-th storage location, and the horizontal coordinate of the storage location is x j , the vertical coordinate of the cargo location is y j , the cargo location coordinates are (x j ,y j , z j ), the model set of the target products is P, P = {1, 2, …, p, …, |P|}, p represents the model of the pth target product; h zj Indicates the level where the cargo location is located, h zj ∈{0,1}, if the jth cargo location is on the zth shelf, h zj =1, otherwise, h zj =0;O op represents the quantity of target product p contained in the order corresponding to order O, Indicates whether the target product p requires material i, , if the target product p requires material i, ,otherwise ;U pi represents the quantity of material i required for the target product p, G ow Indicates whether the wth wave contains the oth order, G ow ∈{0,1}, if the wth wave contains the oth order, G ow =1, otherwise, G ow =0;n oi represents the quantity of material i requested in the oth order; C i represents the capacity of a shelf for material i; M is a large constant; K represents the width of each shelf; H represents the height of each shelf; D represents the depth of each shelf; v1 represents the walking speed of the replenishment object; v2 represents the walking speed of the picking object; x represents the number of shelf rows, y represents the number of shelf columns, and z represents the number of shelf layers; PT z Indicates that the picking is stored in the The duration of the layer of material, PT z is the preset constant, Indicates that the picking is stored in the Ergonomic risks of layered materials, is a preset constant; , if the wave is w and material i is assigned to location j, ,otherwise ; Indicates the target product Need to be from the cargo position Picking materials The number of If the target product Need to be from the cargo position Picking materials , ,otherwise ; Indicates whether the target product p needs to be moved from location j1 ​​to location j2. If the target product p needs to be from the shelf Move to shelf Selection, ,otherwise ; represents the coordinates of the picking platform; T represents the width of each lane in the picking configuration area; Indicates storage in the cargo space Picking distance; Indicates that the picking platform arrives at the cargo location Walking time; Represents the coordinates of the replenishment object; Indicates storage in the cargo space Replenishment distance; Indicates the replenishment object arrives at the location Walking time; Indicates the distance between cargo locations or between the picking platform and cargo locations; represents the walking time between the cargo locations or between the picking platform and the cargo locations; the picking walking time of the target product p is ;The picking walking time for order o is ;The picking operation time of target product p is ; Ergonomic risk of picking objects at each shelf level is ;The total ergonomic risk of picking the target product p is ; Picking orders The total ergonomic risk is ; Indicates any.

[0087] In this embodiment, if there are materials on the cargo position j in the complete picking area that need to be picked, then the picking distance stored in the cargo position j is is the Euclidean distance from the picking platform to the storage location j, and the walking time from the picking platform to the storage location j Picking distance The walking speed of the picker The corresponding definition formula is: , .

[0088] In this embodiment, since the picking mode is complete set picking, the picking object needs to pick all the materials required for a target product and then return to the picking platform. , in the collection Add the starting point and end point, the distance between the cargo locations, and the distance between the picking platform and the cargo locations The walking time between cargo locations and between the picking platform and cargo locations The calculation is similar, and the definition formula is: , .

[0089] In this embodiment, during the replenishment phase, the replenishment distance stored in location j is is the Euclidean distance from the replenisher to the storage location j, and the walking time of the replenisher to the storage location j Picking distance The walking speed of the picker The corresponding definition formula is: , .

[0090] In this embodiment, the minimization of the total replenishment picking operation time PRTT is taken as an optimization goal. The order picking walking time, order picking operation time and order replenishment walking time in the current wave are important components of the total replenishment picking operation time PRTT. The corresponding definition formula is: Target products Picking walking time: .

[0091] Order Picking walking time: .

[0092] Target products Picking operation time: .

[0093] Order Picking operation time: .

[0094] Minimize the total replenishment picking time PRTT:

[0095] In this embodiment, the minimized average ergonomic risk PERT is another optimization goal. The ergonomic risks of the picking objects and replenishment objects during idle activities (i.e., walking) are not considered. In addition, in contrast, the working posture of the replenishment object is relatively simple and has little variation, while the picking object has a complex and changeable working posture due to more picking work. In this embodiment, only the ergonomic risk of the picking object is studied. The total ergonomic risk value of the picking object is determined as the weighted sum of the ergonomic risks of the picking activities, using the duration of its picking operation. As a weight, the average ergonomic risk value is obtained by dividing the total ergonomic risk of the picking order by the total time of the picking operation, and the corresponding definition formula is: Ergonomic risks of picking objects at each shelf level: .

[0096] Picking products Total ergonomic risk of: .

[0097] Picking orders Total ergonomic risk of: .

[0098] Minimized average ergonomic risks: .

[0099] In this embodiment, material allocation restrictions are defined, and each material can be allocated to a storage location. The corresponding definition formula is: .

[0100] In this embodiment, the capacity limit of the cargo location is defined. Each cargo location can only accommodate one material in each wave. The number of materials replenished in each wave does not exceed the storage capacity of each cargo location. The storage capacity of each cargo location is sufficient to accommodate the picked materials. The corresponding definition formula is: ; ; .

[0101] In this embodiment, the quantity requirement limit of product type materials is defined to ensure that the demand for each material is met. The corresponding definition formula is: ; .

[0102] In this embodiment, the path selection restrictions for the picking objects are defined to ensure the path coherence of the picking objects, and the picking objects must start from the picking station, and after arriving at a storage location, they must leave and go to the next storage location for picking, and must return to the picking station after finishing. The corresponding definition formula is: ; ; ; ; .

[0103] In this embodiment, product picking operation constraints are defined and auxiliary variables are introduced , ensure product Pick the material on location j , the corresponding definition formula is: , .

[0104] In this embodiment, the relationship between the storage location allocation and the picking order is defined to ensure that only when the product Need to be picked at the location Materials When the corresponding picking order is generated, the corresponding definition formula is: ; .

[0105] In this embodiment, a limit on the number of directed paths between cargo locations is defined to ensure that there is at most one directed path between two cargo locations. The corresponding definition formula is: .

[0106] This embodiment also provides a picking and replenishment linkage decision-making device that takes ergonomic risks into consideration. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the terms "module", "unit", "sub-unit", etc. may be a combination of software and / or hardware that implements predetermined functions. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0107] Figure 3 is a structural block diagram of a picking and replenishment linkage decision-making device considering ergonomic risks according to an embodiment of the present application, such as Figure 3 As shown, the device includes an acquisition module 31, a processing module 32 and a decision module 33, wherein:

[0108] The acquisition module 31 is used to obtain the aggregate material list information and the storage location information corresponding to the target set picking area from the acquired replenishment picking data stream, determine the first material quantity information to be replenished corresponding to the current wave order according to the aggregate material list information, and perform replenishment picking linkage coding on the first material information to be replenished, the aggregate material list information and the storage location information to generate a first double-coded population, wherein the first double-coded population includes multiple first double-coded individuals.

[0109] The processing module 32 is coupled to the acquisition module 31, and is used to perform a target selection operation corresponding to the preset NSGA-Ⅱ algorithm on the first dual-coded population according to the non-dominated solution parameters and the target congestion corresponding to the first dual-coded individual, to obtain candidate dual-coded individuals, wherein the non-dominated solution parameters are generated by non-dominated sorting based on the individual fitness corresponding to the first dual-coded individual, and the individual fitness includes parameters of the following two dimensions: total operation time for replenishment picking and ergonomic risk score for picking, and the target congestion is calculated jointly according to the total operation time for replenishment picking and the ergonomic risk score for picking corresponding to the first dual-coded individual in the same non-dominated layer.

[0110] The decision module 33 is coupled to the processing module 32, and is used to perform a target genetic operation corresponding to the NSGA-Ⅱ algorithm on all candidate dual-coded individuals, and repeatedly perform the target selection operation and the target genetic operation on all candidate dual-coded individuals generated after completing the target genetic operation, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation.

[0111] In some embodiments, the acquisition module 31 further includes:

[0112] The acquisition unit is used to acquire multiple target materials corresponding to the first material information to be replenished, and determine the storage codes of all storage locations according to the storage location information.

[0113] The generating unit is coupled to the acquiring unit and is used to integer-code a plurality of target materials and storage codes based on the golden storage location allocation strategy, and generate a storage location allocation code corresponding to the replenishment storage location information allocated for each target material.

[0114] The encoding unit is coupled to the generating unit and is used to determine the multiple picking materials corresponding to the target product associated with the aggregate material list, select the storage location allocation codes corresponding to the multiple picking materials corresponding to each target product according to the picking order divided by the codes from all the storage location allocation codes, and perform integer encoding on all the selected storage location allocation codes to obtain a picking sub-code body corresponding to a target product, wherein the order of the storage location allocation codes in the corresponding picking sub-code body represents the order in which the corresponding picking materials are picked, and the picking sub-code body is also used to represent the picking decision information for picking the multiple picking materials corresponding to a target product.

[0115] The combination unit is coupled to the encoding unit and is used to encode all the cargo location allocation codes to generate replenishment code individuals, then encode all the picking sub-code entities to generate picking code individuals, encode the replenishment code individuals and the picking code individuals into the first double-coded individuals, and initialize the population of the first double-coded individuals to generate the first double-coded population.

[0116] In some of the embodiments, the linkage decision device is also used to determine the second dual-coded individual of the current decision iteration, wherein the second dual-coded individual includes one of the following: the first dual-coded individual, and the candidate dual-coded individual generated after completing the target genetic operation corresponding to the previous decision iteration; according to the non-dominated solution parameter corresponding to each second dual-coded individual, the non-dominated layer corresponding to the second dual-coded individual is determined, and the target crowding degree corresponding to each second dual-coded individual in the same non-dominated layer is determined; based on the non-dominated layer and the target crowding degree of the second dual-coded individual, a preset number of second dual-coded individuals are selected one by one from multiple second dual-coded individuals using a tournament selection method to obtain multiple third dual-coded individuals, wherein the third dual-coded individual includes one of the following: a candidate dual-coded individual, and the candidate dual-coded individual generated after completing the current decision iteration.

[0117] In some of the embodiments, the linkage decision-making device is also used to randomly select two second double-coded individuals from multiple second double-coded individuals using a tournament selection method to obtain intended double-coded individuals, and determine whether the two intended double-coded individuals are in the same non-dominated layer; when it is determined that the two intended double-coded individuals are in the same non-dominated layer, the intended double-coded individual with the largest target congestion is used as the corresponding third double-coded individual, and when it is determined that the two intended double-coded individuals are not in the same non-dominated layer, the intended double-coded individual with a higher non-dominated layer is used as the corresponding third double-coded individual; repeatedly perform the operations of selecting two intended double-coded individuals using the tournament selection method and selecting the corresponding third double-coded individual from the two corresponding intended double-coded individuals until a preset number of third double-coded individuals are obtained.

[0118] In some of the embodiments, after obtaining a plurality of third double-coded individuals, the linkage decision device is further used to randomly obtain two third double-coded individuals from the plurality of third double-coded individuals as the parent double-coded individuals currently being processed, and obtain the replenishment code individuals and the picking code individuals corresponding to the two parent double-coded individuals to obtain two candidate parent replenishment code individuals and two candidate parent picking code individuals; divide all the cargo location allocation codes corresponding to the candidate parent replenishment code individuals into a first cross cargo location code group and a first mapping cargo location code group, and combine the first mapping cargo location code group of a corresponding candidate parent replenishment code individual with the first cross cargo location code group of the corresponding other candidate parent replenishment code individual to generate two candidate child replenishment code individuals, and randomly mutate all the cargo location allocation codes of the candidate child replenishment code individuals to generate new child replenishment code individuals; after selecting the picking sub-code bodies corresponding to a plurality of target products from all the picking sub-code bodies of the two candidate parent picking code individuals, all the cargo location allocation codes of the two picking sub-code bodies corresponding to each target product are randomly mutated. The method is divided into a second cross-cargo location coding group and a second mapped cargo location coding group, and the second mapped cargo location coding group corresponding to one of the two picking sub-coding bodies is combined with the second cross-cargo location coding group corresponding to the other picking sub-coding body to generate two new picking sub-coding bodies corresponding to the corresponding target products, and all new picking sub-coding bodies corresponding to the candidate parent picking coding individuals are combined with the unselected picking sub-coding bodies to generate new child picking coding individuals corresponding to the corresponding candidate parent picking coding individuals; after the new child replenishment coding individuals and the corresponding new child picking coding individuals are combined into new child double coding individuals corresponding to the third double coding individuals, all new child double coding individuals and all third double coding individuals are merged into a candidate double coding population, and based on the non-dominated layers and target congestion of all fourth double coding individuals corresponding to the candidate double coding population, a preset number of fourth double coding individuals are selected one by one using the tournament selection method to obtain a new double coding population corresponding to the current decision iteration, and the double coding individuals of the new double coding population are used as the double coding individuals generated after completing the current decision iteration.

[0119] In some of the embodiments, before determining the non-dominated layer corresponding to the second dual-coded individuals according to the non-dominated solution parameters corresponding to each second dual-coded individual, the linkage decision-making device is also used to obtain the total replenishment picking operation time and the picking ergonomic risk score corresponding to the second dual-coded individuals; respectively calculate the first difference of the total replenishment picking operation time and the second difference corresponding to the picking ergonomic risk score corresponding to any two second dual-coded individuals, and respectively judge whether the first difference and the second difference are less than a preset threshold; when it is judged that one of the first difference and the second difference is less than the preset threshold, it is determined that the two second dual-coded individuals are in the same non-dominated layer, and the corresponding non-dominated layer is recorded as the non-dominated solution parameter corresponding to the two second dual-coded individuals.

[0120] In some of the embodiments, the linkage decision device is also used to select two second double-coded individuals adjacent to the corresponding second double-coded individual from all second double-coded individuals in the same non-dominated layer to obtain a fifth double-coded individual and a sixth double-coded individual; determine the operation time crowding distance corresponding to the corresponding second double-coded individual according to the ratio of the third difference of the total replenishment picking operation time corresponding to the fifth double-coded individual and the sixth double-coded individual to the first target time difference, and determine the ergonomic risk crowding distance corresponding to the corresponding second double-coded individual according to the ratio of the fourth difference of the picking ergonomic risk score corresponding to the fifth double-coded individual and the sixth double-coded individual to the first target coefficient difference, wherein the first target time difference is the difference between the maximum and minimum values ​​of the total replenishment picking operation time corresponding to all second double-coded individuals in the same non-dominated layer, and the first target coefficient difference is the difference between the maximum and minimum values ​​of the picking ergonomic risk scores corresponding to all second double-coded individuals in the same non-dominated layer; and take the sum of the operation time crowding distance and the ergonomic risk crowding distance as the target crowding degree corresponding to the corresponding second double-coded individual.

[0121] In some embodiments, after determining the second dual-coded individual of the current decision iteration, the linkage decision device is further used to calculate the corresponding total replenishment picking operation time PRTT according to the following formula: The picking ergonomic risk score PERT is calculated as follows: Calculate the total replenishment picking time PRTT and the picking ergonomic risk score PERT, satisfying the following constraints:

[0122] ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;

[0123] Among them, the target material set is I, I={1,2,…,i,…,|I|}, i represents the i-th target material; the order set corresponding to the aggregate material list is O, O={1,2,…,o,…,|O|}, o represents the o-th aggregate material list; the set of arrival waves of replenishment materials is W, W={1,2,…,w,…,|W|}, w represents the w-th wave; the replenishment object set is R, R={1,2,…,r,…,|R|}, r represents the r-th replenishment object; the picking object set is B, B={1,2,…,b,…,|B|}, b represents the b-th picking object; the storage location set is J, J={1,2,…,j,…,|J|}, j represents the j-th storage location, and the horizontal coordinate of the storage location is x j , the vertical coordinate of the cargo location is y j , the cargo location coordinates are (x j ,y j , z j ), the model set of the target products is P, P = {1, 2, …, p, …, |P|}, p represents the model of the pth target product; h zj Indicates the level where the cargo location is located, h zj ∈{0,1}, if the jth cargo location is on the zth shelf, h zj =1, otherwise, h zj =0;O op represents the quantity of target product p contained in the order corresponding to order O, Indicates whether the target product p requires material i, , if the target product p requires material i, ,otherwise ;U pi represents the quantity of material i required for the target product p, G ow Indicates whether the wth wave contains the oth order, G ow ∈{0,1}, if the wth wave contains the oth order, G ow =1, otherwise, G ow =0;n oi represents the quantity of material i requested in the oth order; C irepresents the capacity of a shelf for material i; M is a large constant; K represents the width of each shelf; H represents the height of each shelf; D represents the depth of each shelf; v1 represents the walking speed of the replenishment object; v2 represents the walking speed of the picking object; x represents the number of shelf rows, y represents the number of shelf columns, and z represents the number of shelf layers; PT z Indicates that the picking is stored in the The duration of the layer of material, PT z is the preset constant, Indicates that the picking is stored in the Ergonomic risks of layered materials, is a preset constant; , if the wave is w and material i is assigned to location j, ,otherwise ; Indicates the target product Need to be from the cargo position Picking materials The number of If the target product Need to be from the cargo position Picking materials , ,otherwise ; Indicates whether the target product p needs to be moved from location j1 ​​to location j2. If the target product p needs to be from the shelf Move to shelf Selection, ,otherwise ; represents the coordinates of the picking platform; T represents the width of each lane in the picking configuration area; Indicates storage in the cargo space Picking distance; Indicates that the picking platform arrives at the cargo location Walking time; Represents the coordinates of the replenishment object; Indicates storage in the cargo space Replenishment distance; Indicates the replenishment object arrives at the location Walking time; Indicates the distance between cargo locations or between the picking platform and cargo locations; represents the walking time between the cargo locations or between the picking platform and the cargo locations; the picking walking time of the target product p is ;The picking walking time for order o is ;The picking operation time of target product p is ; Ergonomic risk of picking objects at each shelf level is ;The total ergonomic risk of picking the target product p is ; Picking orders The total ergonomic risk is ; Indicates any.

[0124] This embodiment further provides a service platform, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0125] Optionally, the service platform may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0126] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0127] S1, after obtaining the aggregate material list information and the storage location information corresponding to the target set picking area from the acquired replenishment picking data stream, determine the first material quantity information to be replenished corresponding to the current wave order according to the aggregate material list information, and perform replenishment picking linkage coding on the first material information to be replenished, the aggregate material list information and the storage location information to generate a first double-coded population, wherein the first double-coded population includes multiple first double-coded individuals.

[0128] S2. According to the non-dominated solution parameters and target congestion corresponding to the first dual-coded individual, the target selection operation corresponding to the preset NSGA-Ⅱ algorithm is performed on the first dual-coded population to obtain candidate dual-coded individuals, wherein the non-dominated solution parameters are generated by non-dominated sorting based on the individual fitness corresponding to the first dual-coded individual. The individual fitness includes parameters of the following two dimensions: total operation time for replenishment picking and ergonomic risk score for picking. The target congestion is calculated jointly based on the total operation time for replenishment picking and ergonomic risk score for picking corresponding to the first dual-coded individual in the same non-dominated layer.

[0129] S3, performing the target genetic operation corresponding to the NSGA-Ⅱ algorithm on all candidate dual-coded individuals, and repeating the target selection operation and the target genetic operation on all candidate dual-coded individuals generated after completing the target genetic operation, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation.

[0130] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0131] In addition, in combination with the method for decision-making in linkage between picking and replenishment considering ergonomic risks in the above embodiments, the present application embodiment can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any one of the methods for decision-making in linkage between picking and replenishment considering ergonomic risks in the above embodiments is implemented.

[0132] A person skilled in the art should understand that the technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0133] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A picking and replenishment linkage decision method considering ergonomic risks, characterized in that: include: After obtaining the aggregate material list information and the storage location information corresponding to the target set picking area from the acquired replenishment picking data stream, determine the first to-be-replenished material quantity information corresponding to the current wave order according to the aggregate material list information, and perform replenishment picking linkage coding on the first to-be-replenished material information, the aggregate material list information and the storage location information to generate a first double-coded population, wherein the first double-coded population includes a plurality of first double-coded individuals; According to the non-dominated solution parameters and target congestion corresponding to the first dual-coded individuals, the target selection operation corresponding to the preset NSGA-Ⅱ algorithm is performed on the first dual-coded population to obtain candidate dual-coded individuals, wherein the non-dominated solution parameters are generated by non-dominated sorting based on the individual fitness corresponding to the first dual-coded individuals, and the individual fitness includes parameters of the following two dimensions: total operation time for replenishment picking and a risk score for picking ergonomics, and the target congestion is calculated jointly according to the total operation time for replenishment picking and the risk score for picking ergonomics corresponding to the first dual-coded individuals in the same non-dominated layer; The target genetic operation corresponding to the NSGA-Ⅱ algorithm is performed on all the candidate dual-coded individuals, and the target selection operation and the target genetic operation are repeatedly performed on all the candidate dual-coded individuals generated after completing the target genetic operation, until a target dual-coded population including at least the target dual-coded individual is generated, and a decision result including the target dual-coded individual is obtained, wherein the target dual-coded individual is a dual-coded individual whose individual fitness is less than a preset fitness threshold, and the target genetic operation includes partial mapping crossover and random mutation.

2. The method according to claim 1, characterized in that The first to-be-replenished material information, the aggregated material list information and the storage location information are coded for replenishment and picking linkage to generate a first double-coded population, including: Acquire multiple target materials corresponding to the first material information to be replenished, and determine the storage codes of all storage locations according to the storage location information; Based on the golden storage location allocation strategy, multiple target materials and the storage codes are integer-coded to generate a storage location allocation code corresponding to the replenishment storage location information allocated to each target material; Determine the multiple picking materials corresponding to the target product associated with the aggregate material list, select the shelf allocation codes corresponding to the multiple picking materials corresponding to each of the target products from all the shelf allocation codes according to the picking order divided by the codes, and perform integer encoding on all the selected shelf allocation codes to obtain a picking sub-code body corresponding to one of the target products, wherein the order of the shelf allocation codes in the corresponding picking sub-code body represents the order in which the corresponding picking materials are picked, and the picking sub-code body is also used to represent the picking decision information for picking the multiple picking materials corresponding to one of the target products; After encoding all of the cargo location allocation codes to generate replenishment code individuals, all of the picking sub-code entities are encoded to generate picking code individuals, the replenishment code individuals and the picking code individuals are encoded as the first double-coded individuals, and the first double-coded individuals are initialized as a population to generate the first double-coded population.

3. The method according to claim 2, characterized in that The method further comprises: Determine a second dual-coded individual of the current decision iteration, wherein the second dual-coded individual includes one of the following: the first dual-coded individual, the candidate dual-coded individual generated after completing the target genetic operation corresponding to the previous decision iteration; Determine a non-dominated layer corresponding to the second dual-coded individual according to the non-dominated solution parameter corresponding to each of the second dual-coded individuals, and determine the target congestion degree corresponding to each of the second dual-coded individuals in the same non-dominated layer; Based on the non-dominated layer of the second dual-coded individuals and the target congestion, a preset number of the second dual-coded individuals are selected one by one from the plurality of the second dual-coded individuals using a tournament selection method to obtain a plurality of third dual-coded individuals, wherein the third dual-coded individuals include one of the following: the candidate dual-coded individuals, the alternative dual-coded individuals generated after completing the current decision iteration.

4. The method according to claim 3, characterized in that Based on the non-dominated layer of the second dual-coded individuals and the target congestion degree, a preset number of the second dual-coded individuals are selected one by one from a plurality of the second dual-coded individuals by using a tournament selection method, including: Using a tournament selection method, randomly selecting two of the second dual-coded individuals from a plurality of the second dual-coded individuals to obtain intended dual-coded individuals, and determining whether the two intended dual-coded individuals are in the same non-dominated layer; When it is determined that the two intended dual-coded individuals are in the same non-dominated layer, the intended dual-coded individual with the largest target congestion is used as the corresponding third dual-coded individual; and when it is determined that the two intended dual-coded individuals are not in the same non-dominated layer, the intended dual-coded individual with a higher non-dominated layer is used as the corresponding third dual-coded individual; Repeat the operations of selecting two of the intended double-coded individuals using the tournament selection method and selecting the corresponding third double-coded individual from the two corresponding intended double-coded individuals until a preset number of the third double-coded individuals are obtained.

5. The method according to claim 3, characterized in that: After obtaining a plurality of third double-coded individuals, the method further comprises: Two third double-coded individuals randomly obtained from the plurality of third double-coded individuals are used as the parent double-coded individuals currently being processed, and the replenishment coding individuals and the picking coding individuals corresponding to the two parent double-coded individuals are obtained to obtain two candidate parent replenishment coding individuals and two candidate parent picking coding individuals; Divide all the cargo location allocation codes corresponding to the candidate parent replenishment code individuals into a first cross cargo location code group and a first mapping cargo location code group, and combine the first mapping cargo location code group of a corresponding candidate parent replenishment code individual with the first cross cargo location code group of another corresponding candidate parent replenishment code individual to generate two candidate child replenishment code individuals, and randomly mutate all the cargo location allocation codes of the candidate child replenishment code individuals to generate new child replenishment code individuals; After selecting the picking sub-coding bodies corresponding to a plurality of the target products from all the picking sub-coding bodies of the two candidate parent picking coding individuals, all the storage location allocation codes of the two picking sub-coding bodies corresponding to each target product are divided into a second cross storage location code group and a second mapping storage location code group, and the second mapping storage location code group corresponding to one of the two picking sub-coding bodies is combined with the second cross storage location code group corresponding to the other picking sub-coding body to generate two new picking sub-coding bodies corresponding to the corresponding target products, and all the new picking sub-coding bodies corresponding to the candidate parent picking coding individuals are combined with the picking sub-coding bodies that have not been selected to generate a new child picking coding individual corresponding to the corresponding candidate parent picking coding individual; After the new offspring replenishment coded individuals and the corresponding new offspring picking coded individuals are combined into new offspring double coded individuals corresponding to the third double coded individuals, all the new offspring double coded individuals and all the third double coded individuals are merged into a candidate double coded population, and based on the non-dominated layers of all fourth double coded individuals corresponding to the candidate double coded population and the target congestion, a preset number of the fourth double coded individuals are selected one by one using the tournament selection method to obtain a new double coded population corresponding to the current decision iteration, and the double coded individuals of the new double coded population are used as the double coded individuals generated after completing the current decision iteration.

6. The method according to claim 3, characterized in that Before determining the non-dominated layer corresponding to the second dual-coded individual according to the non-dominated solution parameter corresponding to each of the second dual-coded individuals, the method further includes: Obtain the total replenishment picking operation time and the picking ergonomic risk score corresponding to the second dual-coded individual; Calculate respectively the first difference of the total replenishment picking operation time and the second difference of the picking ergonomic risk score corresponding to any two of the second dual-coded individuals, and determine respectively whether the first difference and the second difference are less than a preset threshold; When it is determined that one of the first difference and the second difference is less than a preset threshold, it is determined that the two second dual-coded individuals are in the same non-dominated layer, and the corresponding non-dominated layer is recorded as the non-dominated solution parameter corresponding to the two second dual-coded individuals.

7. The method according to claim 6, characterized in that Determining the target congestion degree corresponding to each of the second dual-coded individuals in the same non-dominated layer includes: Selecting two second double-coded individuals adjacent to the corresponding second double-coded individual from all the second double-coded individuals in the same non-dominated layer to obtain a fifth double-coded individual and a sixth double-coded individual; According to the ratio of the third difference of the total replenishment picking operation time corresponding to the fifth dual-coded individual and the sixth dual-coded individual to the first target time difference, the operation time crowding distance corresponding to the corresponding second dual-coded individual is determined, and according to the ratio of the fourth difference of the picking ergonomic risk score corresponding to the fifth dual-coded individual and the sixth dual-coded individual to the first target coefficient difference, the ergonomic risk crowding distance corresponding to the corresponding second dual-coded individual is determined, wherein the first target time difference is the difference between the maximum value and the minimum value of the total replenishment picking operation time corresponding to all the second dual-coded individuals in the same non-dominated layer, and the first target coefficient difference is the difference between the maximum value and the minimum value of the picking ergonomic risk score corresponding to all the second dual-coded individuals in the same non-dominated layer; The sum of the working time crowding distance and the ergonomic risk crowding distance is used as the target crowding degree corresponding to the corresponding second dual-coded individual.

8. The method according to claim 3, characterized in that After determining the second dual-coded individual of the current decision iteration, the method includes: The corresponding total replenishment picking operation time PRTT is calculated according to the following formula: The picking ergonomic risk score PERT is calculated as follows: The total replenishment picking time PRTT and the picking ergonomic risk score PERT are calculated to meet the following constraints: ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； Among them, the target material set is I, I={1,2,…,i,…,|I|}, i represents the i-th target material; the order set corresponding to the aggregate material list is O, O={1,2,…,o,…,|O|}, o represents the o-th aggregate material list; the set of arrival waves of replenishment materials is W, W={1,2,…,w,…,|W|}, w represents the w-th wave; the replenishment object set is R, R={1,2,…,r,…,|R|}, r represents the r-th replenishment object; the picking object set is B, B={1,2,…,b,…,|B|}, b represents the b-th picking object; the storage location set is J, J={1,2,…,j,…,|J|}, j represents the j-th storage location, and the horizontal coordinate of the storage location is x j , the vertical coordinate of the cargo location is y j , the cargo location coordinates are (x j ,y j , z j ), the model set of the target products is P, P = {1, 2, …, p, …, |P|}, p represents the model of the pth target product; h zj Indicates the level where the cargo location is located, h zj ∈{0,1}, if the jth cargo location is on the zth shelf, h zj =1, otherwise, h zj =0;O op represents the quantity of target product p contained in the order corresponding to order O, Indicates whether the target product p requires material i, , if the target product p requires material i, ,otherwise ;U pi represents the quantity of material i required for the target product p, G ow Indicates whether the wth wave contains the oth order, G ow ∈{0,1}, if the wth wave contains the oth order, G ow =1, otherwise, G ow =0;n oi represents the quantity of material i requested in the oth order; C i represents the capacity of a shelf for material i; M is a large constant; K represents the width of each shelf; H represents the height of each shelf; D represents the depth of each shelf; v1 represents the walking speed of the replenishment object; v2 represents the walking speed of the picking object; x represents the number of shelf rows, y represents the number of shelf columns, and z represents the number of shelf layers; PT z Indicates that the picking is stored in the The duration of the layer of material, PT z is the preset constant, Indicates that the picking is stored in the Ergonomic risks of layered materials, is a preset constant; , if the wave is w and material i is assigned to location j, ,otherwise ; Indicates the target product Need to be from the cargo position Picking materials The number of If the target product Need to be from the cargo position Picking materials , ,otherwise ; Indicates whether the target product p needs to be moved from location j1 ​​to location j2. If the target product p needs to be from the shelf Move to shelf Selection, ,otherwise ; represents the coordinates of the picking platform; T represents the width of each lane in the picking configuration area; Indicates storage in the cargo space Picking distance; Indicates that the picking platform arrives at the cargo location Walking time; Represents the coordinates of the replenishment object; Indicates storage in the cargo space Replenishment distance; Indicates the replenishment object arrives at the location Walking time; Indicates the distance between cargo locations or between the picking platform and cargo locations; represents the walking time between the cargo locations or between the picking platform and the cargo locations; the picking walking time of the target product p is ;The picking walking time for order o is ;The picking operation time of target product p is ; Ergonomic risk of picking objects at each shelf level is ;The total ergonomic risk of picking the target product p is ; Picking orders The total ergonomic risk is ; Indicates any.

9. A service platform, comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps of the picking and replenishment linkage decision-making method considering ergonomic risks according to any one of claims 1 to 8.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the picking and replenishment linkage decision-making method considering ergonomic risks described in any one of claims 1 to 8 are implemented.

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