Method for generating order picking wave order and electronic equipment
By setting multiple filtering dimension information in the combined wave planning template configuration interface and generating the combined wave planning template, the problems of cumbersome and inflexible combined wave operations in the existing technology are solved, and more efficient picking task generation and timeliness satisfaction are achieved.
Patent Information
- Application Number
- CN202410698284.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-05-31
- Publication Date
- 2025-02-28
AI Technical Summary
In the prior art, combined wave operation needs to be performed manually, and the operation is cumbersome and not flexible enough, making it difficult to meet the task requirements with high timeliness, resulting in the inability to fulfill the contract on time.
By providing a combined wave plan template configuration interface, users are allowed to set a variety of optional filtering dimension information, including grid warehouse attributes, product attributes, product sales attributes and picking partition attributes, generate appropriate combined wave plan templates, and automatically execute combined wave plan, filter out orders and products that meet the conditions, and generate picking tasks.
It improves the combined wave efficiency, reduces manual operations, better meets timeliness requirements, and ensures that orders are fulfilled on time.
Smart Images
Figure CN119539672A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of information processing technology, and in particular to a method and electronic device for generating picking waves. Background Art
[0002] In the commodity information service system of the community group purchase model, a three-level warehouse distribution model consisting of "shared warehouse-central warehouse-grid warehouse" is usually adopted. In this model, suppliers deliver goods to shared warehouses, then centrally distribute them to central warehouses, and then transfer goods to grid warehouses in various regions according to user orders, and finally deliver them to the user's designated pick-up point by the grid warehouse.
[0003] Among them, in the process of transferring from the central warehouse to the grid warehouse, it is usually necessary to perform wave combining processing, that is, the picking needs of goods in the same operation direction (which may be the same grid warehouse or multiple grid warehouses with similar routes) are combined according to the strategy to generate a batch of picking tasks, carry out the picking operations together, and then transfer them to the grid warehouse together.
[0004] In the related prior art, this wave combining operation usually needs to be performed manually by the planner of the central warehouse. Specifically, the planner needs to formulate an operation plan in advance and determine which types of orders are to be picked for each of the multiple operation time periods. For example, from 14:00 to 15:00, picking tasks are performed for "hot products", from 15:00 to 16:00, picking tasks are performed for frozen goods, and so on. Then, the planner can enter the screening conditions for each operation time period through the relevant operation interface, including information on fields such as delivery time and fulfillment period. The system will perform a preliminary screening from the orders that have not yet been picked according to this screening condition, and select the orders that meet the conditions. After that, the planner will manually select the orders belonging to the categories of "hot products" and "frozen goods" from these preliminary screened orders, and then combine these orders into the same wave to perform the picking operation together.
[0005] The above manual combining process is complicated and not flexible enough. It may not meet the needs of some tasks with high timeliness requirements, resulting in failure to fulfill the contract on time. Summary of the invention
[0006] The present application provides a method and electronic device for generating picking waves, which can improve efficiency and better meet the picking needs of orders with higher timeliness requirements.
[0007] This application provides the following solutions:
[0008] A method for generating picking waves for order requirements, comprising:
[0009] After receiving a request for formulating a consolidation plan for a target central warehouse, determining a consolidation plan template corresponding to the target central warehouse; the consolidation plan template is generated in the following manner: providing an operation option for setting a picking time period and a filtering condition under each time period through a configuration interface, and after receiving an operation for setting the filtering condition under the target time period through the operation option, providing a plurality of optional filtering dimension information, the plurality of optional filtering dimension information including grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering condition by selecting the plurality of optional filtering dimensions and setting corresponding attribute values, and generating a corresponding consolidation plan template;
[0010] The generated combined plan template is parsed to determine the filtering dimensions involved in the filtering conditions of the current time period, and the attribute values of the multiple orders to be picked associated with the target central warehouse on the corresponding filtering dimensions are obtained, so as to filter out multiple orders that meet the filtering conditions of the current time period from the multiple orders to be picked, and generate picking tasks for the goods associated with the multiple orders.
[0011] Among them, the multiple optional screening dimension information is determined after enumerating multiple different personalized combining requirements that multiple different central warehouses may have.
[0012] Among them, the configuration interface also includes: operating options for setting multiple different picking priorities for the same time period, and setting screening conditions for the multiple different picking priorities respectively, so as to generate multiple different picking tasks corresponding to multiple different picking priorities for the same time period.
[0013] Among them, the configuration interface also includes: operating options for setting picking task generation rules, so as to set corresponding picking task generation rules according to the picking priority, and the picking task generation rules include multiple preset optional rules, which are used to set the upper and lower limits of order quantity, upper and lower limits of commodity quantity, upper and lower limits of container loading capacity, upper and lower limits of pallet ratio and / or picking tool requirements in the picking task.
[0014] Wherein, the grid bin attributes include attributes related to grid bin line grouping;
[0015] The commodity attributes include commodity packaging related attributes and commodity characteristic label attributes related to picking;
[0016] The commodity sales attributes include attributes related to the sales ranking of the commodity.
[0017] The step of obtaining the attribute values of the plurality of to-be-picked orders associated with the target central warehouse on the corresponding screening dimensions includes:
[0018] The attribute values of the order to be picked under the grid warehouse attribute, the commodity attribute, the commodity sales attribute and / or the picking partition attribute are queried from a plurality of different data sources respectively.
[0019] A device for generating picking waves, comprising:
[0020] A template determination unit is used to determine a consolidation plan template corresponding to the target central warehouse after receiving a request for formulating a consolidation plan for the target central warehouse; the consolidation plan template is generated in the following manner: providing an operation option for setting a picking time period and a filtering condition under each time period through a configuration interface, and providing a plurality of optional filtering dimension information after receiving an operation for setting the filtering condition under the target time period through the operation option, wherein the plurality of optional filtering dimension information includes grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering condition by selecting the plurality of optional filtering dimensions and setting corresponding attribute values, and generate a corresponding consolidation plan template;
[0021] The combined plan fulfillment execution unit is used to parse the generated combined plan template, determine the filtering dimensions involved in the filtering conditions of the current time period, and obtain the attribute values of the multiple orders to be picked associated with the target central warehouse on the corresponding filtering dimensions, so as to filter out multiple orders that meet the filtering conditions of the current time period from the multiple orders to be picked, and generate picking tasks for the goods associated with the multiple orders.
[0022] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of any of the methods described above.
[0023] An electronic device, comprising:
[0024] one or more processors; and
[0025] A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of any of the methods described above.
[0026] A computer program product comprises a computer program / computer executable instructions, wherein the computer program / computer executable instructions implement the steps of any of the aforementioned methods when executed by a processor in an electronic device.
[0027] According to the specific embodiments provided in this application, this application discloses the following technical effects:
[0028] Through the embodiment of the present application, a consolidation plan template configuration interface can be provided through the consolidation plan management system, and a variety of optional filtering dimension information can be provided, and the various optional filtering dimension information can include grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes. In this way, for a specific central warehouse, multiple picking time periods can be set through the above configuration interface, and filtering conditions can be set for each picking time period. The specific filtering conditions can be set by the above multiple optional filtering dimensions and corresponding attribute values. Since the filtering dimensions can involve grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, etc., very specific filtering conditions can be combined, and the system can automatically execute the corresponding consolidation plan template later, filter out orders and commodities that meet the filtering conditions, and generate corresponding picking tasks. For users such as consolidators, it is only necessary to set the filtering conditions for each time period, and there is no need to check the orders one by one. The system can automatically complete the consolidation and generate picking tasks, so efficiency can be improved and timeliness and other requirements can be better met.
[0029] Of course, any product implementing the present application does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0031] Figure 1 This is a schematic diagram of the operation interface of manual wave combining in the prior art;
[0032] Figure 2 It is a schematic diagram of the system architecture provided by the embodiment of the present application;
[0033] Figure 3 is a flow chart of the method provided in the embodiment of the present application;
[0034] Figure 4 is a schematic diagram of a template generation interface provided in an embodiment of the present application;
[0035] Figure 5 is a schematic diagram of a device provided in an embodiment of the present application;
[0036] Figure 6 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0037] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.
[0038] In order to facilitate understanding of the specific implementation scheme provided by the embodiments of the present application, it is first necessary to explain that in the commodity information service system of the community group purchase model, the specific service model is usually that the supplier stores the goods in the central warehouses in multiple regions in advance. After the consumer places an order online, the corresponding grid warehouse can be determined according to the offline service store selected by the consumer, and then it can be reversed to the corresponding central warehouse. Then, according to the consumer's order (including the goods associated with the specific order, the selected delivery time, etc.), the central warehouse picks the goods and transfers them to the grid warehouse. After that, the grid warehouse delivers the goods to the offline service store, waiting for the user to pick up the goods, or the offline service store provides door-to-door delivery service for consumers, etc. Among them, the grid warehouse is a transit warehouse that links the community group purchase platform and the offline service store (self-pickup point).
[0039] Among them, in the process of picking goods by the central warehouse and transferring goods to the grid warehouse, since the same central warehouse is usually associated with multiple grid warehouses, each grid warehouse is respectively associated with its own consumer orders, the goods associated with each order, the required delivery time, etc. may be different. Therefore, when picking goods and transferring goods in the central warehouse, it is necessary to formulate a suitable consolidation plan so that the relevant goods can be delivered to the grid warehouse in time, while avoiding or reducing the waste of picking and transfer resources, and meeting the timeliness requirements of some orders or goods.
[0040] For example, multiple grid warehouses corresponding to the same central warehouse have different distances from the central warehouse. However, some orders associated with these grid warehouses may have the same timeliness requirements. Therefore, the grid warehouses that are farther away may need to be given priority in picking and transfer operations.
[0041] Alternatively, there are usually multiple different picking zones in the central warehouse, each of which stores a lot of goods. However, different picking zones may have very different picking strategies. Some zones may need to use refrigerated equipment for picking and need to pick up first, while other zones can just pick normally and therefore can pick up later.
[0042] In addition, in community group buying scenarios, since the specific commodities are usually fruits, vegetables, fresh produce, etc., the commodities themselves may also have some characteristics related to picking, such as easy to thaw, fragile, easy to leak, easy to break, etc. When picking, different picking tools may be required for commodities with different characteristics. For example, commodities that are easy to thaw may need to be picked using refrigerated trucks, etc. Therefore, commodities with the same characteristics may need to be picked at the same time, etc.
[0043] Furthermore, different central warehouses usually have different picking strategies. For example, the distribution of grid warehouses associated with different central warehouses is different, and the picking zone deployment within the central warehouse may also be different. Different central warehouses need to formulate personalized consolidation plans according to their own circumstances.
[0044] In summary, the existence of the above situations leads to many factors that need to be considered when formulating a wave combining plan, and each central warehouse has its own personalized wave combining requirements. It is precisely because of the existence of the above situation that the wave combining operators of each central warehouse need to perform manual wave combining operations in the prior art. For example, the specific operation interface can be as follows Figure 1 As shown, although there is a simple automatic filtering function, it is usually only a rough screening on more common fields such as grid warehouse, delivery date, and fulfillment period. After that, the wave combiner needs to manually check the actual situation of each filtered order one by one, including the attributes of the associated goods, the route of the grid warehouse, the attributes of the picking partition where the corresponding goods are located in the central warehouse, etc., and then determine whether it is possible to pick within a certain time period. If so, the order needs to be checked. After selecting multiple orders that can be picked within the same time period, these orders can be merged into the same wave and picked within the time period. However, the above-mentioned method of manually combining waves by wave combiners is relatively inefficient. For some orders with high timeliness requirements, they may be delayed due to failure to be discovered in time, etc.
[0045] Therefore, in an embodiment of the present application, a multi-dimensional demand selection and matching architecture for warehouse wave task calculation is provided, which aims to pre-screen and match order items that meet the needs for wave task generation in complex environments. In addition, although multiple central warehouses have their own personalized wave combining needs, they can also achieve automated wave task generation through the same system, rather than relying on the manual selection of orders by combiners for wave combining operations.
[0046] In order to achieve the above purpose, a specific consolidation plan template configuration interface can be provided in the embodiment of the present application, and the configuration interface can provide operation options for setting multiple picking time periods and setting filtering conditions for each time period. Among them, in order to enable each central warehouse to formulate a consolidation plan template according to its own personalized needs, the embodiment of the present application can enumerate all possible filtering dimensions according to the various personalized consolidation needs that may be possessed by multiple different central warehouses, specifically, grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, etc., and can also provide a variety of optional attribute values for various attributes. In this way, when formulating a consolidation plan template for a specific central warehouse, the picking time period can be configured according to the configuration interface, and the filtering conditions can be configured for each time period respectively. Such filtering conditions can be generated by selecting or combining the above multiple different filtering dimensions. For example, a certain time period needs to include a certain grid warehouse attribute, but needs to exclude a certain commodity attribute, another time period needs to include a certain commodity sales attribute, but needs to exclude a certain picking partition attribute, etc., which can be set according to the above various attributes pre-defined in the system. In addition, the specific grid warehouse attributes may include multiple specific attributes, such as the grid warehouse grouping identifier, group identifier, grid warehouse route identifier, etc.; the product attributes may also include multiple specific attributes, such as whether the product has various characteristic tags, etc. Therefore, by combining these screening dimensions, a variety of different screening conditions can be combined to meet the various personalized synthesis needs of different central warehouses.
[0047] After determining the consolidation plan template, when fulfilling the consolidation plan, the consolidation plan template corresponding to the specific central word can be parsed to determine the corresponding filtering conditions in the current time period. Such filtering conditions can be expressed through information such as the attribute values on one or more filtering dimensions defined above. Afterwards, for the multiple orders in the state of waiting to be picked associated with the current central warehouse, automatic data acquisition is performed, and the data is matched and judged with the filtering conditions to determine whether they meet the filtering conditions of the current time period. If they meet the conditions, they can be added to the picking wave corresponding to the current time period. Among them, the attribute values of a specific order in multiple filtering dimensions can be obtained by querying a variety of different databases. In other words, the embodiment of the present application supports query operations on a variety of different databases. For example, the commodity attributes mainly query the commodity information database, the commodity sales attributes need to query the database related to the order information, and so on. For each order to be picked, different databases can be queried separately, or the attribute values of a specific order in multiple different dimensions can be matched and judged with the filtering conditions. Among them, regarding the attribute values of specific orders in various dimensions, the attribute values related to the attributes of the goods, that is, the attribute values of the goods associated with the order, and the attribute values related to the attributes of the grid warehouse, that is, the relevant attribute values of the corresponding grid warehouse determined according to the self-pickup point information associated with the specific order, and the pre-saved association relationship information between each grid warehouse and the self-pickup point, etc. For example, the screening condition corresponding to a certain time period is: including a certain grid warehouse grouping identifier, excluding a certain product attribute, then the grouping identifiers of the grid warehouses corresponding to each order to be picked can be queried, and the product attributes of the goods contained in the order, and then it can be determined whether the above screening conditions are met, and so on. After screening out multiple orders that meet the conditions, they can be combined into the same wave in the same time period, and then the corresponding picking tasks are generated.
[0048] In addition, in an optional implementation, an operation option for setting multiple picking priorities included in the same time period can also be provided in the configuration interface, so that in the process of combining waves according to the combining plan template corresponding to the same time period, multiple orders in the same wave can also be divided into multiple groups according to different picking priorities, and each group can generate a picking task. In other words, the same time period corresponds to the same wave, but the same wave can generate multiple different picking tasks.
[0049] Furthermore, since specific orders are generated by consumers, the number of orders screened out according to specific consolidation plans or priority rules is not fixed, but will change according to the actual ordering situation of consumers. However, the number of orders and the number of goods that can be supported in the same picking task are usually limited. Therefore, in the specific implementation, operation options for configuring the picking task generation rules can also be provided in the configuration interface. In addition, regarding the specific picking task generation rules, various possible generation rules can also be enumerated in advance, and the corresponding rule numbers are given respectively. During the setting process, the specific rule number can be selected. For example, for a picking task of a certain priority, you can use generation rules No. 1 and No. 2, and so on. In the process of selecting a specific rule number, the rule details corresponding to each rule number can also be displayed to facilitate user selection.
[0050] From the perspective of system architecture, see Figure 2 , the embodiment of the present application can provide a consolidation plan management system, which can be provided to the central warehouse for use. Multiple central warehouses associated with the same commodity information service system can formulate their own consolidation plan templates through the consolidation plan management system, and the consolidation plan template can be parsed to realize the automatic fulfillment of the consolidation plan. Among them, the above system supports setting specific screening conditions on multiple different screening dimensions. Specifically, multiple optional screening dimensions can be pre-defined, which can include grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, etc. Candidate attribute values can also be provided for various attributes. In this way, according to the situation of the specific central warehouse, the corresponding screening conditions can be selected from one or some attributes and saved in the database. Specifically, when executing a specific consolidation plan, the above system can determine the screening conditions corresponding to the specific central warehouse in the current time period from the database, and query the attribute values of each order to be picked on the corresponding attributes respectively. In the specific query process, it can involve query processing of multiple different databases such as the commodity information database and the order information database. After the relevant attribute value data is queried, it can be matched with the screening conditions to determine whether it meets the screening conditions of the current time period.
[0051] The specific implementation scheme provided in the embodiments of the present application is described in detail below.
[0052] First, the present application embodiment provides a method for generating a picking wave, see Figure 3 , the method may include:
[0053] S301: After receiving a request for formulating a consolidation plan for a target central warehouse, determine a consolidation plan template corresponding to the target central warehouse; the consolidation plan template is generated in the following manner: providing operation options for setting picking time periods and filtering conditions under each time period through a configuration interface, and after receiving an operation for setting filtering conditions under a target time period through the operation options, providing a variety of optional filtering dimension information, the various optional filtering dimension information including grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering conditions by selecting the various optional filtering dimensions and setting corresponding attribute values, and generate a corresponding consolidation plan template.
[0054] The execution subject of each step of the embodiment of the present application is the aforementioned consolidation plan management system, and users such as consolidators of each central warehouse can use the system to formulate a consolidation plan template for a specific central warehouse. In the process of formulating the template, a related configuration interface can be displayed, in which operation options for setting multiple picking time periods can be provided, and operation options for setting the screening conditions under each time period can also be provided. For example, Figure 4 As shown, it shows the configuration interface of the combined plan template provided in the embodiment of the present application, wherein multiple time periods have been set as shown in 41. For each time period, the orders that need to be excluded or included can be set through the logical relationships such as "exclude" and "include".
[0055] When setting the filtering conditions for a specific time period, a variety of optional filtering dimension information can be provided, wherein, as mentioned above, the specific filtering dimension information can include grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering conditions by selecting a variety of optional filtering dimensions and setting corresponding attribute values, and generate a corresponding consolidation plan. For example, a consolidation plan can be formulated for the time period of 12:00-19:00, and a certain attribute can be selected and the attribute value can be set on the corresponding "reject", "include" and other fields. Among them, in the specific implementation, the various optional filtering dimension information can be determined after enumerating a variety of different personalized consolidation requirements that may be possessed by a plurality of different central warehouses, so as to meet the personalized needs of different central warehouses.
[0056] Among them, grid warehouse attributes, product attributes, product sales attributes and picking partition attributes can be further subdivided. For example, grid warehouse attributes can include multiple attributes related to grid warehouse line grouping; product attributes can include attributes related to product packaging, product feature label attributes related to picking, etc.; product sales attributes can include attributes related to product sales ranking (for example, it can be used to determine whether it is a "hot product", etc.). More specifically, each screening dimension can include:
[0057] 1. Grid warehouse grouping can be set by "equal to" or "not equal to". Multiple selections are allowed. Candidate values include grid warehouse group, grid warehouse transportation route group, first-level network group, etc.
[0058] 2. Grid bin container grouping can be set by "equal to" or "not equal to". Multiple selections are allowed. Candidate values include normal temperature container group, temperature controlled container group, etc.
[0059] 3. Grid warehouse line grouping can be set by "equal to" or "not equal to". Multiple selections are allowed, and the candidate value is the line name of the current warehouse;
[0060] 4. Grid warehouse, you can set it by "equal to" or "not equal to", you can select multiple, and the candidate value is the name of the grid warehouse that is not disabled when the current warehouse is connected;
[0061] 5. Rounds can be set by "equal to" or "not equal to". Multiple selections are allowed. The candidate value is the round number configured for the current warehouse.
[0062] 6. ABC classification can be set by "equal to" or "not equal to". Multiple selections are allowed. The candidate value is the ABC classification value of the current warehouse.
[0063] 7. Special product classification can be set by "equal to" or "not equal to". Multiple selections are allowed. The candidate value is the special product classification value of the current warehouse.
[0064] 8. Product sales volume can be input through "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc. Only values greater than 0 are allowed, decimals are allowed, and the rationality of the input value needs to be verified; unit: piece, box, pallet. Among them, this demand attribute only judges the sales volume according to the SKU (minimum inventory unit) dimension;
[0065] 9. Product sales ranking, you can enter values by setting "first", "last", etc., and only integers greater than 0 are allowed;
[0066] 10. Sales ranking of picking area, you can input values by setting "first", "last", etc., and only integers greater than 0 are allowed;
[0067] 11. For the remaining demand, you can enter the value by setting "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc. Only values greater than 0 are allowed, decimals are allowed, and the rationality of the input value needs to be verified; unit: piece, box, pallet;
[0068] 12. The remaining demand for a single grid warehouse can be input through "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc. Only values greater than 0 are allowed, decimals are allowed, and the rationality of the input value needs to be verified; unit: piece, box, pallet;
[0069] 13. Whether it is sold out, you can set it by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0070] 14. Whether it is sold out, you can set it by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0071] 15. Box size, you can enter the value by setting "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc., and only integers greater than 0 are allowed;
[0072] 16. For the support rule, you can set the input value by "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc. Only integers greater than 0 are allowed to be entered;
[0073] 17. Single piece weight (kg), you can enter the value by setting "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc., and only values greater than 0 are allowed (decimals can be entered);
[0074] 18. Weight of the whole box (kg). You can enter the value by setting "greater than", "greater than or equal to", "equal to", "not equal to", "less than", "less than or equal to", etc. Only values greater than 0 are allowed (decimals can be entered);
[0075] 19. Packaging method, which can be set by "equal to" or "not equal to", multiple selection, candidate values are box packaging, plastic film packaging, box packaging, woven bag packaging, plastic bag packaging, etc.;
[0076] 20. FEFO (First Expired First Out) products can be set by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0077] 21. Fragile items can be set by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0078] 22. Leakable liquid, can be set by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0079] 23. Fragile, can be set by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0080] 24. Easy to thaw, can be set by "equal to" or "not equal to", single choice, candidate values are yes and no;
[0081] 25. Item type can be set by "equal to" or "not equal to". Multiple selections are available. The candidate value is the item type enumeration value.
[0082] 26. Operation mode can be set by "equal to" or "not equal to". Multiple selections are available. The candidate values are picking only and sowing only.
[0083] 27. Flowers and green plants can be set by "equal to" or "not equal to", single choice, and the candidate values are yes and no.
[0084] Through the above-mentioned rich and diverse screening dimensions, a variety of different screening conditions can be combined to meet the various personalized needs of different central warehouses when combining waves.
[0085] In addition, the configuration interface may also include: an operation option for setting multiple different picking priorities for the same time period, and setting filtering conditions for the multiple different picking priorities, so as to generate multiple different picking tasks corresponding to the multiple different picking priorities for the same time period. Figure 4 As shown in 43 of , multiple different priorities can be set for the same time period, where the priority names can be customized by users such as the combiner to facilitate user distinction. In addition, different filtering conditions can be set for different priorities, which can also include fields such as "include" and "exclude", and specific filtering dimensions and corresponding attribute values can be set on the corresponding fields. It should be noted that when setting filtering conditions for the same time period, if multiple priorities need to be set, Figure 4 As shown in 42, the template may also include a "whole elimination" field for a specific time period, and "elimination" and "inclusion" fields for specific priorities. During the setting process, some orders may be eliminated as a whole first, and then specific screening conditions may be set for specific priorities through "elimination" and "inclusion". Among them, the setting of priorities may usually be performed on the attribute dimension related to the goods, that is, after eliminating some orders through "whole elimination" and the like, for the remaining qualified orders, the set priorities may be used to determine which goods in the order shall be picked first, which may be picked later, or which may be picked at the same time, and so on.
[0086] Furthermore, the configuration interface may also include: an operation option for setting picking task generation rules, so as to set the picking task generation rules corresponding to the picking priority, and the picking task generation rules include a plurality of preset optional rules, so as to respectively set the upper and lower limits of the order quantity, the upper and lower limits of the commodity quantity, the upper and lower limits of the container loading, the upper and lower limits of the pallet ratio and / or the picking tool requirements in the picking task. Figure 4 As shown at 44 in the figure, a specific picking task generation rule can be selected in the "Issuing Task" field, for example, the first priority of the first time period is selected as 1, 2, etc. In the process of selecting a specific rule number, the specific rule details can also be displayed to facilitate the user's selection. For example, the generation rule numbered "1" can be "single grid warehouse-single product-whole picking-whole pallet-fruit picking", etc.
[0087] S302: Analyze the generated combined plan template to determine the filtering dimensions involved in the filtering conditions of the current time period, and obtain the attribute values of the multiple orders to be picked associated with the target central warehouse on the corresponding filtering dimensions, so as to filter out multiple orders that meet the filtering conditions of the current time period from the multiple orders to be picked, and generate picking tasks for the goods associated with the multiple orders.
[0088] After completing the formulation of the combined wave plan template, you can enter the subsequent fulfillment execution stage. During the fulfillment execution process, the system can parse the generated combined wave plan template to determine the filtering dimensions involved in the filtering conditions of the current time period. For example, a certain time period may involve filtering conditions set by grid warehouse attributes, commodity attributes, and commodity sales attributes, then the attribute values corresponding to the above grid warehouse attributes, commodity attributes, and commodity sales attributes of multiple orders to be picked associated with the target central warehouse can be obtained. For example, the grid warehouse to which it belongs can be determined based on the pick-up point associated with a certain order, and then the attribute values of the specific grid warehouse can be obtained from the database related to the warehouse information, such as the identification of the grid warehouse grouping, the line information to which the grid warehouse belongs, etc.; In addition, some commodities will be associated with the specific order, so the relevant data of the specific commodity can also be obtained, including whether it is an easy-to-freeze product, a fragile product, whether it is a "hot product", etc. That is to say, in an embodiment of the present application, when performing data query, it can support querying from a variety of different databases to obtain the attribute values of the order to be picked under the grid warehouse attributes, product attributes, product sales attributes and / or picking partition attributes, and then compare them with specific screening conditions.
[0089] It should be noted that in the specific implementation, the same order may include a variety of different products. When matching according to the attributes related to the products, an order can be divided into multiple waves of operations, and different products in an order may have different priorities, generating different picking tasks. Of course, after the picking task is completed, there are subsequent operations such as collection review and shipment. After that, different products in the same order can be transferred to the grid warehouse together.
[0090] In summary, through the embodiment of the present application, a consolidation plan template configuration interface can be provided through the consolidation plan management system, and a variety of optional filtering dimension information can be provided, and the various optional filtering dimension information can include grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes. In this way, for a specific central warehouse, multiple picking time periods can be set through the above configuration interface, and filtering conditions can be set for each picking time period. The specific filtering conditions can be set by the above multiple optional filtering dimensions and corresponding attribute values. Since the filtering dimensions can involve grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, etc., very specific filtering conditions can be combined, and the system can automatically execute the corresponding consolidation plan template later, filter out orders and commodities that meet the filtering conditions, and generate corresponding picking tasks. For users such as consolidators, it is only necessary to set the filtering conditions for each time period, and there is no need to check the orders one by one. The system can automatically complete the consolidation and generate picking tasks, so efficiency can be improved and timeliness and other requirements can be better met.
[0091] It should be noted that the embodiments of the present application may involve the use of user data. In actual applications, user-specific personal data can be used in the scheme described herein within the scope permitted by applicable laws and regulations, subject to the requirements of applicable laws and regulations of the country where the user is located (for example, with the user's explicit consent, effective notification to the user, etc.).
[0092] Corresponding to the method embodiment, the present application embodiment also provides a device for generating picking waves, see Figure 5 , the device may include:
[0093] The template determination unit 501 is used to determine the consolidation plan template corresponding to the target central warehouse after receiving a request for formulating a consolidation plan for the target central warehouse; the consolidation plan template is generated in the following manner: providing an operation option for setting the picking time period and the filtering conditions under each time period through a configuration interface, and providing a plurality of optional filtering dimension information after receiving an operation for setting the filtering conditions under the target time period through the operation option, wherein the plurality of optional filtering dimension information includes grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering conditions by selecting the plurality of optional filtering dimensions and setting corresponding attribute values, and generate a corresponding consolidation plan template;
[0094] The combined plan fulfillment execution unit 502 is used to parse the generated combined plan template, determine the filtering dimensions involved in the filtering conditions of the current time period, and obtain the attribute values of the multiple orders to be picked associated with the target central warehouse on the corresponding filtering dimensions, so as to filter out multiple orders that meet the filtering conditions of the current time period from the multiple orders to be picked, and generate picking tasks for the goods associated with the multiple orders.
[0095] Among them, the multiple optional screening dimension information is determined after enumerating multiple different personalized combining requirements that multiple different central warehouses may have.
[0096] The configuration interface also includes: operating options for setting multiple different picking priorities for the same time period, and setting screening conditions for the multiple different picking priorities respectively, so as to generate multiple different picking tasks corresponding to the multiple different picking priorities for the same time period.
[0097] Alternatively, the configuration interface also includes: operating options for setting picking task generation rules, so as to set corresponding picking task generation rules according to the picking priority, and the picking task generation rules include multiple preset optional rules for setting the upper and lower limits of order quantity, upper and lower limits of commodity quantity, upper and lower limits of container loading capacity, upper and lower limits of pallet ratio and / or picking tool requirements in the picking task.
[0098] Wherein, the grid bin attributes include attributes related to grid bin line grouping;
[0099] The commodity attributes include commodity packaging related attributes and commodity characteristic label attributes related to picking;
[0100] The commodity sales attributes include attributes related to the sales ranking of the commodity.
[0101] Specifically, the combined wave plan fulfillment execution unit can be used to:
[0102] The attribute values of the order to be picked under the grid warehouse attribute, the commodity attribute, the commodity sales attribute and / or the picking partition attribute are queried from a plurality of different data sources respectively.
[0103] In addition, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods in the aforementioned method embodiments are implemented.
[0104] And an electronic device, comprising:
[0105] one or more processors; and
[0106] A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of the method described in any one of the aforementioned method embodiments.
[0107] A computer program product includes a computer program / computer executable instructions, which, when executed by a processor in an electronic device, implement the steps of the method described in the aforementioned method embodiment.
[0108] in, Figure 6 The architecture of the electronic device is shown as an example, which may include a processor 610, a video display adapter 611, a disk drive 612, an input / output interface 613, a network interface 614, and a memory 620. The processor 610, the video display adapter 611, the disk drive 612, the input / output interface 613, the network interface 614, and the memory 620 may be communicatively connected via a communication bus 630.
[0109] Among them, the processor 610 can be implemented by a general-purpose CPU (Central Processing Unit, processor), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, etc., to execute relevant programs to implement the technical solution provided in this application.
[0110] The memory 620 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 620 can store an operating system 621 for controlling the operation of the electronic device 600, and a basic input and output system (BIOS) for controlling the low-level operation of the electronic device 600. In addition, a web browser 623, a data storage management system 624, and a picking wave generation processing system 625, etc. can also be stored. The above-mentioned picking wave generation processing system 625 can be an application program that specifically implements the operations of the aforementioned steps in the embodiment of the present application. In short, when the technical solution provided by the present application is implemented by software or firmware, the relevant program code is stored in the memory 620 and is called and executed by the processor 610.
[0111] The input / output interface 613 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.
[0112] The network interface 614 is used to connect to a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).
[0113] The bus 630 comprises a pathway for transmitting information between the various components of the device (eg, the processor 610, the video display adapter 611, the disk drive 612, the input / output interface 613, the network interface 614, and the memory 620).
[0114] It should be noted that, although the above device only shows a processor 610, a video display adapter 611, a disk drive 612, an input / output interface 613, a network interface 614, a memory 620, a bus 630, etc., in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include components necessary for implementing the solution of the present application, and does not necessarily include all the components shown in the figure.
[0115] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.
[0116] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.
[0117] The above is a detailed introduction to the method and electronic device for generating picking waves provided by the present application. This article uses specific examples to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application. At the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present application.
Claims
1. A method for generating picking waves for order requirements, characterized in that: include: After receiving a request for formulating a wave combining plan for a target central warehouse, determining a wave combining plan template corresponding to the target central warehouse; The consolidation plan template is generated in the following manner: providing an operation option for setting a picking time period and a filtering condition in each time period through a configuration interface, and providing a plurality of optional filtering dimension information after receiving an operation for setting the filtering condition in a target time period through the operation option. The plurality of optional filtering dimension information includes grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering condition by selecting the plurality of optional filtering dimensions and setting corresponding attribute values, and generate a corresponding consolidation plan template; The generated combined plan template is parsed to determine the filtering dimensions involved in the filtering conditions of the current time period, and the attribute values of the multiple orders to be picked associated with the target central warehouse on the corresponding filtering dimensions are obtained, so as to filter out multiple orders that meet the filtering conditions of the current time period from the multiple orders to be picked, and generate picking tasks for the goods associated with the multiple orders.
2. The method according to claim 1, characterized in that The multiple optional screening dimension information is determined after enumerating multiple different personalized combining requirements that multiple different central warehouses may have.
3. The method according to claim 1, characterized in that The configuration interface also includes: operating options for setting multiple different picking priorities for the same time period, and setting screening conditions for the multiple different picking priorities respectively, so as to generate multiple different picking tasks corresponding to the multiple different picking priorities for the same time period.
4. The method according to claim 3, characterized in that The configuration interface also includes: operation options for setting picking task generation rules, so as to set corresponding picking task generation rules according to the picking priority, and the picking task generation rules include multiple preset optional rules, which are used to set the upper and lower limits of order quantity, upper and lower limits of commodity quantity, upper and lower limits of container loading, upper and lower limits of pallet ratio and / or picking tool requirements in the picking task.
5. The method according to claim 1, characterized in that The grid bin attributes include attributes related to grid bin line grouping; The commodity attributes include commodity packaging related attributes and commodity characteristic label attributes related to picking; The commodity sales attributes include attributes related to the commodity sales ranking.
6. The method according to claim 1, characterized in that The obtaining of the attribute values of the plurality of to-be-picked orders associated with the target central warehouse on the corresponding screening dimensions includes: The attribute values of the order to be picked under the grid warehouse attribute, the commodity attribute, the commodity sales attribute and / or the picking partition attribute are queried from a plurality of different data sources respectively.
7. A device for generating picking waves, characterized in that: include: A template determination unit, configured to determine a wave combining plan template corresponding to the target central warehouse after receiving a request for formulating a wave combining plan for the target central warehouse; The consolidation plan template is generated in the following manner: providing an operation option for setting a picking time period and a filtering condition in each time period through a configuration interface, and providing a plurality of optional filtering dimension information after receiving an operation for setting the filtering condition in a target time period through the operation option. The plurality of optional filtering dimension information includes grid warehouse attributes, commodity attributes, commodity sales attributes, and picking partition attributes, so as to set the filtering condition by selecting the plurality of optional filtering dimensions and setting corresponding attribute values, and generate a corresponding consolidation plan template; The combined plan fulfillment execution unit is used to parse the generated combined plan template, determine the filtering dimensions involved in the filtering conditions of the current time period, and obtain the attribute values of the multiple orders to be picked associated with the target central warehouse on the corresponding filtering dimensions, so as to filter out multiple orders that meet the filtering conditions of the current time period from the multiple orders to be picked, and generate picking tasks for the goods associated with the multiple orders.
8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 6 are implemented.
9. An electronic device, characterized in that: include: one or more processors; as well as A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of the method described in any one of claims 1 to 6.
10. A computer program product comprising a computer program / computer executable instructions, characterized in that: When the computer program / computer executable instructions are executed by a processor in an electronic device, the steps of the method according to any one of claims 1 to 6 are implemented.