Task allocation management method and device

Abstract

The invention discloses a task allocation management method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the steps of obtaining each article identifier in a plurality of orders; determining a branch pile corresponding to each article identifier according to a preset rule; determining a task list corresponding to each sub-heap according to the task list group single parameter and each sub-heap; and determining a set order corresponding to each task order according to the set order group order parameter and each task order, and allocating a picking task according to the set order and the task order. According to the implementation mode, the development difficulty of the set order and task order building logic is reduced, decoupling of task order building and set order building is achieved, the flexibility is high, the method is suitable for multi-industry personalized service scenes, the saturation degree of the task order and the set order can be improved, the labor cost is reduced, and the order picking efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and apparatus for managing task allocation. Background Technology

[0002] In a warehouse management system, pickers can execute picking tasks based on the task orders corresponding to the collection orders, and then distribute the items after the picking tasks are completed to fulfill the order's outbound processing. Collection orders and task orders are generated by combining multiple orders. In related technologies, the combination logic for collection orders and task orders is generally based on threshold-based grouping, exhibiting high coupling at the code level. This limits the order combination function, resulting in poor compatibility with diverse industry-specific business scenarios and low flexibility. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a task allocation management method and apparatus, which can reduce the development difficulty of the logic for assembling collection orders and task orders, achieve decoupling of task orders and collection order assemblies, have high flexibility, are applicable to personalized business scenarios in multiple industries, can increase the saturation of task orders and collection orders, reduce labor costs, and improve picking efficiency.

[0004] To achieve the above objectives, according to one aspect of the present invention, a task allocation management method is provided, comprising:

[0005] Retrieve the item identifiers from multiple orders;

[0006] The corresponding pile for each item identifier is determined according to preset rules;

[0007] The task order corresponding to each sub-stack is determined based on the single parameter of the task order group and each sub-stack.

[0008] Based on the parameters of the collection order and each task order, determine the collection order corresponding to each task order, and allocate picking tasks according to the collection order and the task order.

[0009] Optionally, the task order group has multiple single parameters; determining the task order corresponding to each sub-stack based on the task order group single parameters and each sub-stack includes:

[0010] Retrieve the group single parameter value corresponding to each task group single parameter in each sub-heap;

[0011] Based on the single parameter values ​​of each group and the upper limit threshold of the single parameter of each task group, the single parameter of the target group of the task is determined from the single parameters of multiple task groups.

[0012] Based on the task order target grouping parameters, group each sub-stack into tasks and determine the task order corresponding to each sub-stack.

[0013] Optionally, the set of single parameters can be multiple, and the set corresponding to each task order is determined based on the set of single parameters and each task order, including:

[0014] Retrieve the group parameter value corresponding to each set of group parameters in each task order;

[0015] Based on the single parameter values ​​of each group and the upper limit threshold of the single parameter of each set, the single parameter of the target group is determined from multiple single parameters of sets;

[0016] Based on the set target group parameters, each task order is grouped into a set, and the set corresponding to each task order is determined.

[0017] Optionally, the task order is grouped into groups for each sub-stack according to the task order target grouping parameters, and the task order corresponding to each sub-stack is determined, including:

[0018] Obtain the identifiers of each item in the pile;

[0019] Obtain the target group single parameter value corresponding to the target group single parameter of the task order for each item identifier in the pile;

[0020] Based on the single parameter values ​​of each target group and the upper limit threshold of the single parameter of the target group of the task order, the task order corresponding to each item identifier in the pile is determined, so as to determine the task order corresponding to the pile.

[0021] Optionally, determining the task order corresponding to each item identifier in the pile includes:

[0022] Identify the first item in the pile whose single parameter value of the target group is greater than or equal to the upper threshold.

[0023] Based on the single parameter value of the target group and the upper limit threshold, one or more task orders corresponding to the first item identifier are determined.

[0024] Optionally, determining the task order corresponding to each item identifier in the pile further includes:

[0025] Identify the identifiers of each second item in the pile whose single parameter value of the target group is less than the upper threshold.

[0026] Each second item identifier is treated as an array, and the arrays are sorted according to the single parameter value of the target group in each array;

[0027] Based on the sorting results, determine the task order corresponding to each array, and then determine the task order corresponding to each of the second item identifiers.

[0028] Optionally, the sorting result is that each array is sorted in ascending order according to the single parameter value of the target group; determining the task sheet corresponding to each array based on the sorting result includes:

[0029] Calculate the sum of the target group single parameter values ​​of the first n arrays in the sorting. If the calculation result is greater than the upper limit threshold, divide the first n-1 arrays into a group to obtain each group. The sum of the target group single parameter values ​​of each array in each group is taken as the target group single parameter value of the group. Wherein, n is a natural number greater than 1.

[0030] Determine the distance between each of the other groups (excluding the first group) and the upper limit threshold, and sort the other groups in ascending order of distance;

[0031] Based on the group single parameter value of each of the other sorted groups, the group single parameter value of each array in the first group, and the upper limit threshold, the first group is split to obtain the updated groups.

[0032] The task sheet corresponding to each array is determined based on the updated groupings.

[0033] According to another aspect of the present invention, a task allocation management device is provided, comprising:

[0034] The module retrieves the identifiers of each item from multiple orders.

[0035] The first determination module determines the corresponding pile for each item identifier according to preset rules;

[0036] The second determination module determines the task order corresponding to each sub-stack based on the single parameter of the task order group and each sub-stack.

[0037] The third determining module determines the collection order corresponding to each task order based on the collection order parameters and each task order, so as to allocate picking tasks according to the collection order and the task order.

[0038] According to another aspect of the present invention, an electronic device is provided, comprising:

[0039] One or more processors;

[0040] Storage device for storing one or more programs.

[0041] When the one or more programs are executed by the one or more processors, the one or more processors implement the task allocation management method provided by the present invention.

[0042] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the task allocation management method provided by the present invention.

[0043] One embodiment of the above invention has the following advantages or beneficial effects: The task allocation management method of this invention obtains the item identifiers from multiple orders, firstly groups the item identifiers according to preset rules, then groups each group according to task order grouping parameters to obtain task orders; and then groups each task order according to collection order grouping parameters to obtain collection orders, thereby realizing task allocation management. This method is applicable to the formation of task orders and collection orders in various business scenarios, decoupling the task order and collection order formation logic, using a splitting algorithm for order formation, adjusting for extreme data, increasing the saturation of task orders and collection orders, reducing labor costs, and improving picking efficiency; moreover, this method is universal, has low development difficulty and cost, and is easy to implement.

[0044] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0045] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein:

[0046] Figure 1 This is a schematic diagram of the main flow of a task allocation management method according to an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of the main flow of a task allocation management method according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the main flow of a task allocation management method according to an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the main modules of a task allocation management device according to an embodiment of the present invention;

[0050] Figure 5 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied;

[0051] Figure 6 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0052] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0053] Figure 1 This is a schematic diagram of the main flow of a task allocation management method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method includes the following steps:

[0054] Step S101: Obtain the item identifiers from multiple orders;

[0055] Step S102: Determine the corresponding pile for each item identifier according to preset rules;

[0056] Step S103: Determine the task order corresponding to each sub-stack based on the single parameters of the task order group and each sub-stack;

[0057] Step S104: Determine the collection order corresponding to each task order based on the collection order parameters and each task order, so as to allocate picking tasks according to the collection order and the task order.

[0058] In this embodiment of the invention, the task allocation management method can be applied to the grouping of task orders and collection orders in different business scenarios of different industries in the warehouse management system, so as to allocate task orders to pickers to perform picking tasks, meet business needs, reduce labor costs, and improve picking efficiency.

[0059] In this embodiment of the invention, the item identifiers of multiple orders are first obtained. These multiple orders can be orders used to create a combined order, and can be obtained according to specified rules. For example, the multiple orders can be orders placed within a preset time range, or orders where the items are stored in the same storage area. Each order can include one or more item identifiers (such as SKUs). Each item identifier has a corresponding quantity of items and corresponding item attributes, including item volume, item weight, and may also include item color, style, etc.

[0060] In this embodiment of the invention, after obtaining the item identifiers from multiple orders, the item identifiers are grouped according to preset rules to obtain a group corresponding to each item identifier. The preset rules can be mutually exclusive rules to achieve grouping of different item identifiers. For example, in a clothing warehouse handling enterprise orders, the enterprise requires that after outbound orders arrive at offline stores, all SKUs be categorized by style for easy display and temporary storage. Therefore, when allocating tasks in the warehouse, SKUs need to be grouped by style for picking and packing by style. That is, the preset rules can be clothing style, color, etc. The preset rules can be customized according to the needs of different business scenarios.

[0061] In this embodiment of the invention, after determining the pile corresponding to each item identifier, various piles corresponding to multiple orders are obtained, and each pile corresponds to one or more item identifiers. Then, each pile is grouped into orders according to the task order grouping parameters to obtain various task orders for task allocation. The task order grouping parameters are parameters used to create task orders. One or more task order grouping parameters can be configured, and they can include item type, item volume, item weight, and item quantity in the task order. Each task order grouping parameter has an upper limit threshold, i.e., a maximum threshold, such as an upper limit threshold for item type, item volume, item weight, and item quantity.

[0062] In this embodiment of the invention, the task order group single parameter can be any one of the item type, item volume, item weight, and item quantity. Based on the task order group single parameter and each sub-pile, the task order corresponding to each sub-pile is determined. Then, each sub-pile can be grouped directly according to the upper limit threshold of the task order group single parameter to determine each sub-pile.

[0063] The task order group parameters can be multiple of the following: item type, item volume, item weight, and item quantity. The task order corresponding to each sub-pile is determined based on the task order group parameters and each sub-pile. One of the multiple task order group parameters can be randomly selected as the target group parameter of the task order. Then, the task order is obtained by grouping each item identifier in each sub-pile according to the upper limit threshold of the target group parameter.

[0064] In this embodiment of the invention, there are multiple single parameters for a task order group; determining the task order corresponding to each sub-stack based on the single parameters of the task order group and each sub-stack includes:

[0065] Retrieve the group single parameter value corresponding to each task group single parameter in each sub-heap;

[0066] Based on the single parameter values ​​of each group and the upper limit threshold of the single parameter of each task group, the single parameter of the target group of the task is determined from the single parameters of multiple task groups.

[0067] Based on the task order target grouping parameters, group each sub-stack into tasks and determine the task order corresponding to each sub-stack.

[0068] In this embodiment of the invention, the task order grouping parameters can be multiple of the following: item type, item volume, item weight, and item quantity. The grouping parameter values ​​corresponding to the task order grouping parameters in each sub-pile are obtained, such as the results for item type, item volume, item weight, and item quantity for each sub-pile. Then, based on the upper limit value of each task order grouping parameter, the number of task orders obtained by grouping the sub-piles according to each task order grouping parameter is determined. The task order grouping parameter with the fewest task orders is taken as the target grouping parameter. Then, grouping is performed on each sub-pile according to the upper limit threshold of the target grouping parameter to obtain the task orders corresponding to each sub-pile. For example, grouping the sub-piles according to item type and its upper limit threshold yields 10 task orders, grouping them according to item volume and its upper limit threshold yields 15 task orders, grouping them according to item weight and its upper limit threshold yields 12 task orders, and grouping them according to item quantity and its upper limit threshold yields 8 task orders. In this case, the item quantity can be used as the target grouping parameter for grouping the sub-piles.

[0069] In this embodiment of the invention, grouping each sub-stack according to the task order target grouping parameters and determining the task order corresponding to each sub-stack includes:

[0070] Retrieve the identifiers of each item in the pile;

[0071] Retrieve the target group single parameter value corresponding to the target group single parameter of the task order for each item identifier in the pile;

[0072] Based on the single parameter values ​​of each target group and the upper limit threshold of the single parameter of the target group in the task order, the task order corresponding to each item identifier in the pile is determined, so as to determine the task order corresponding to the pile.

[0073] In this embodiment of the invention, when grouping each sub-pile according to the task order target grouping parameter, the identifiers of each item in each sub-pile are obtained. Then, the target grouping parameter value corresponding to the task order target grouping parameter for each item identifier in the sub-pile is obtained. For example, if the task order target grouping parameter is the number of items, the result of the number of items corresponding to each item identifier in the sub-pile is obtained. Then, the sub-pile is grouped according to the result of the number of items for each item identifier and the upper limit threshold of the task order target grouping parameter to obtain the task order corresponding to each item identifier. If the upper limit threshold is 10 items in each task order, and the sum of the number of items for each item identifier in the sub-pile is 10, then the sub-pile can be determined as a task order.

[0074] In embodiments of the present invention, such as Figure 2 As shown, the task order corresponding to each item identifier in the pile is determined, including:

[0075] Step S201: Determine the identifier of the first item in the stack whose single parameter value of the target group is greater than or equal to the upper limit threshold;

[0076] Step S202: Based on the single parameter value of the target group and the upper limit threshold, determine one or more task orders corresponding to the first item identifier.

[0077] In this embodiment of the invention, the task order corresponding to each item identifier in the pile is determined based on the single parameter value of each target group and the upper limit threshold of the single parameter of the target group in the task order. Specifically, if the pile includes a first item identifier whose single parameter value of the target group is greater than or equal to the upper limit threshold, the task order corresponding to the item identifier can be determined by calculating the quotient of the single parameter value of the target group and the upper limit threshold. That is, the quotient obtained is the number of task orders. For example, if the single parameter of the target group of the task order is the number of items and the upper limit threshold is 10, and the pile includes a first item identifier with a quantity of 25 items, then the quotient of the quantity of the first item identifier and the upper limit threshold is 2. Therefore, two task orders can be obtained based on the first item identifier, and each task order includes 10 first item identifiers.

[0078] In embodiments of the present invention, such as Figure 3 As shown, determining the task order corresponding to each item identifier in the pile also includes:

[0079] Step S301: Identify the identifiers of each second item in the pile whose single parameter value of the target group is less than the upper limit threshold;

[0080] Step S302: Sort each array based on the single parameter value of the target group, using each second item identifier as an array;

[0081] Step S303: Determine the task order corresponding to each array based on the sorting result, so as to determine the task order corresponding to each second item identifier.

[0082] In this embodiment of the invention, for second item identifiers whose target grouping parameter value in the stack is less than the upper limit threshold, grouping can be performed on each item identifier according to the upper limit threshold. That is, grouping multiple item identifiers together yields a task order, thereby increasing the saturation of the task order and improving picking efficiency. Each second item identifier can be treated as an array, and the arrays can be sorted according to the size of the target grouping parameter value, such as in ascending order. Then, grouping can be performed based on the sorting results to obtain the task order corresponding to each item identifier.

[0083] For example, the sum of the target group single parameter values ​​of the first and last sorted arrays can be calculated. If the sum of the target group single parameter values ​​equals the upper threshold, they can be grouped into one task. If the sum of the target group single parameter values ​​is less than the upper threshold, the sum of the target group single parameter values ​​of the second and last sorted arrays can be calculated. If the sum of the target group single parameter values ​​equals the upper threshold, they can be grouped into one task. If the target group single parameter value is greater than the upper threshold, the last sorted array is taken as one task, and the sum of the target group single parameter values ​​of the first and second-to-last sorted arrays can be calculated. If the sum of the target group single parameter values ​​equals the upper threshold, they can be grouped into one task. This process continues until the task corresponding to each array is determined.

[0084] In this embodiment of the invention, after determining one or more task orders corresponding to the first item identifier, the target group order parameter value of the first item identifier is updated according to the target group order parameter value and the upper limit threshold. Specifically, the product of the number of task orders and the upper limit threshold is calculated, and the difference between the target group order parameter value and the product result is used as the updated target group order parameter value of the first item identifier, that is, the remaining target group order parameter value of the first item identifier after grouping. In other words, the first item identifier can be a second item identifier whose target group order parameter value is less than or equal to the upper limit threshold, that is, each second item identifier includes the first item identifier.

[0085] In this embodiment of the invention, the sorting result is that each array is sorted in ascending order according to the single parameter value of the target group; determining the task order corresponding to each array based on the sorting result includes:

[0086] Calculate the sum of the target group single parameter values ​​of the first n arrays sorted. If the calculation result is greater than the upper limit threshold, divide the first n-1 arrays into a group to obtain each group; use the sum of the target group single parameter values ​​of each array in each group as the target group single parameter value of the group.

[0087] Determine the distance between each group other than the first group and the upper limit threshold, and sort the other groups in ascending order of distance;

[0088] Based on the group single parameter value of each of the other sorted groups, the group single parameter value of each array in the first group, and the upper limit threshold, the first group is split to obtain the updated groups;

[0089] The task sheet corresponding to each array is determined based on the updated groupings.

[0090] In this embodiment of the invention, each array is sorted in ascending order according to the single parameter value of the target group. Then, a splitting algorithm is used to group each array. Specifically, the single parameter values ​​of the target group of the first n arrays are summed. If the summation result is equal to the upper threshold, the first n arrays are grouped to obtain the corresponding task order. If the summation result is less than the upper threshold, it is continued to be summed with the array next in order. If the summation result is greater than the upper threshold, the first n-1 arrays are grouped as one group. Then, starting from the nth array, the single parameter values ​​of the target group of the subsequent arrays are summed in order to determine each group. The single parameter value of the target group of each group is calculated, that is, the summation result of the single parameter values ​​of the target group of each array in each group is calculated, where n is a natural number greater than 1.

[0091] After determining the groups, except for the first group, calculate the distance between each other group and the upper threshold. This involves calculating the difference between the target group single parameter value and the upper threshold for each other group. Sort the other groups in ascending order of difference. Then, use a splitting algorithm to split the first group. Specifically, sum the target parameter value of the other group with the smallest difference with the largest target group single parameter value in the first group. If the sum equals the upper threshold, the group becomes a single task, and the other groups are re-sorted in ascending order of difference. If the sum is greater than the upper threshold, the group is split into two groups. The second-largest single-parameter value of the target group in the first group is summed. If the sum with the smallest single-parameter value of the target group in the first group is greater than the upper threshold, the array with the smallest difference is taken as a task order. If the sum is less than the upper threshold, the array with the largest single-parameter value of the target group in the first group is added to the other group with the smallest difference. Then, the other groups are re-sorted in ascending order of difference to obtain updated groups. Based on the updated groups, the first group is split again until the task order corresponding to each array is determined, and then the task orders corresponding to each stack are determined. By grouping the arrays into tasks through the splitting algorithm, adjustments are made for extreme data, the saturation of task orders is increased, thereby improving picking efficiency and reducing picking costs.

[0092] In this embodiment of the invention, after obtaining each task order, the task orders are grouped according to the set order grouping parameters to obtain the set order corresponding to each task order. The set order grouping parameters can be configured as one or more, for example, they can be configured as one or more of order quantity, item volume, item weight, and item quantity. If the set order grouping parameter is one of order quantity, item volume, item weight, and item quantity, the task orders can be directly grouped according to the upper limit threshold of the set order grouping parameter to obtain the set order corresponding to each task order. If the set order grouping parameter is multiple of order quantity, item volume, item weight, and item quantity, one can be randomly selected as the target set order grouping parameter, and then the task orders are grouped according to the upper limit threshold of the target set order grouping parameter to obtain the various set orders.

[0093] In this embodiment of the invention, there are multiple single parameters for a single set of tasks. The set of tasks corresponding to each task is determined based on the single parameters of the single set of tasks and each task task, including:

[0094] Retrieve the group parameter value corresponding to each set of group parameters in each task order;

[0095] Based on the single parameter values ​​of each group and the upper limit threshold of the single parameter of each set, the single parameter of the target group is determined from multiple single parameters of sets;

[0096] Based on the target group parameters of the set, each task is grouped into a set, and the set corresponding to each task is determined.

[0097] In this embodiment of the invention, there can be multiple group parameters for a single task order, such as multiple of the following: order quantity, item volume, item weight, and item quantity. The group parameter value corresponding to each group parameter in each task order can be obtained, such as the result of the order quantity, item volume, item weight, and item quantity in each task order. Then, based on the value of each group parameter and the upper limit threshold of each group parameter, the number of group orders corresponding to grouping each task order according to each group parameter is determined. Then, the group parameter with the fewest group orders is used as the target group parameter. Grouping is performed on each task order according to the target group parameter to obtain the group order corresponding to each task order, thereby completing the group order and task order composition of multiple orders to achieve task allocation.

[0098] The task allocation management method of this invention first obtains the item identifiers from multiple orders and groups them according to preset rules; then, it groups each group according to task order grouping parameters to obtain task orders; finally, it groups each task order according to set order grouping parameters to obtain set orders, thus realizing task allocation management. This method is applicable to the creation of task orders and set orders in various business scenarios, decoupling the logic of task order and set order creation. It uses a splitting algorithm for order grouping, adjusts for extreme data, improves the saturation of task orders and set orders, reduces labor costs, and improves picking efficiency. Furthermore, this method is universal, has good compatibility, low development difficulty and cost, and is easy to implement.

[0099] According to another aspect of the embodiments of the present invention, such as Figure 4 As shown, a task allocation management device 400 is provided, comprising:

[0100] Module 401 retrieves the identifiers of each item from multiple orders;

[0101] The first determining module 402 determines the corresponding pile for each item identifier according to preset rules;

[0102] The second determining module 403 determines the task order corresponding to each sub-stack based on the single parameter of the task order group and each sub-stack.

[0103] The third determining module 404 determines the collection order corresponding to each task order based on the collection order parameters and each task order, so as to allocate picking tasks according to the collection order and the task order.

[0104] In this embodiment of the invention, there are multiple task order group parameters; the second determining module 403 is further configured to: obtain the group parameter value corresponding to each task order group parameter in each sub-stack; determine the task order target group parameter from multiple task order group parameters according to each group parameter value and the upper limit threshold of each task order group parameter; group each sub-stack according to the task order target group parameter to determine the task order corresponding to each sub-stack.

[0105] In this embodiment of the invention, there are multiple single parameters in a single set. The third determining module 404 is further configured to: obtain the group parameter value corresponding to each single parameter in each task order; determine the target single parameter from multiple single parameters based on each single parameter value and the upper limit threshold of each single parameter; group each task order according to the target single parameter to determine the single set corresponding to each task order.

[0106] In this embodiment of the invention, the second determining module 403 is further configured to: obtain each item identifier in the pile; obtain the target group single parameter value corresponding to the target group single parameter of the task order for each item identifier in the pile; and determine the task order corresponding to each item identifier in the pile based on the target group single parameter value and the upper limit threshold of the target group single parameter of the task order, so as to determine the task order corresponding to the pile.

[0107] In this embodiment of the invention, the second determining module 403 is further configured to: determine a first item identifier whose target group single parameter value is greater than or equal to the upper limit threshold in the stack; and determine one or more task orders corresponding to the first item identifier based on the target group single parameter value and the upper limit threshold.

[0108] In this embodiment of the invention, the second determining module 403 is further configured to: determine each second item identifier in the stack whose target group single parameter value is less than the upper limit threshold; take each second item identifier as an array and sort each array according to the target group single parameter value of each array; determine the task order corresponding to each array according to the sorting result, so as to determine the task order corresponding to each second item identifier.

[0109] In this embodiment of the invention, the sorting result is that each array is sorted in ascending order according to the single parameter value of the target group; the second determining module 403 is further used for:

[0110] Calculate the sum of the target group single parameter values ​​of the first n arrays sorted. If the result is greater than the upper limit threshold, divide the first n-1 arrays into groups to obtain each group. The sum of the target group single parameter values ​​of each array in each group is taken as the target group single parameter value of the group. Here, n is a natural number greater than 1.

[0111] Determine the distance between each group other than the first group and the upper limit threshold, and sort the other groups in ascending order of distance;

[0112] Based on the group parameter values ​​of each of the other sorted groups, the group parameter values ​​of each array in the first group, and the upper limit threshold, the first group is split to obtain updated groups; the task order corresponding to each array is determined based on the updated groups.

[0113] According to another aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the task allocation management method provided by the present invention.

[0114] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the task allocation management method provided by the present invention.

[0115] Figure 5 An exemplary system architecture 500 is shown, to which the task allocation management method or task allocation management device of the present invention can be applied.

[0116] like Figure 5 As shown, system architecture 500 may include terminal devices 501, 502, and 503, a network 504, and a server 505. Network 504 serves as the medium for providing communication links between terminal devices 501, 502, and 503 and server 505. Network 504 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0117] Users can use terminal devices 501, 502, and 503 to interact with server 505 via network 504 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 501, 502, and 503, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0118] Terminal devices 501, 502, and 503 can be various electronic devices with displays that support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0119] Server 505 can be a server that provides various services, such as a backend management server that supports shopping websites browsed by users using terminal devices 501, 502, and 503 (for example only). The backend management server can analyze and process data such as received product information query requests, and feed back the processing results (such as target push information, product information - for example only) to the terminal device.

[0120] It should be noted that the task allocation management method provided in this embodiment of the invention is generally executed by server 505, and correspondingly, the task allocation management device is generally set in server 505.

[0121] It should be understood that Figure 5 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0122] The following is for reference. Figure 6 It shows a schematic diagram of the structure of a computer system 600 suitable for implementing a terminal device of the present invention. Figure 6 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0123] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 602 or programs loaded from storage section 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the system 600. The CPU 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0124] The following components are connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed.

[0125] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by central processing unit (CPU) 601, it performs the functions defined above in the system of this invention.

[0126] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0127] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0128] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor can be described as including an acquisition module, a first determining module, a second determining module, and a third determining module. The names of these modules do not necessarily limit the module itself; for example, the acquisition module can also be described as "a module for acquiring the identifiers of various items in multiple orders."

[0129] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to include: acquiring item identifiers from multiple orders; determining a stack corresponding to each item identifier according to preset rules; determining a task order corresponding to each stack according to task order group parameters and each stack; and determining a collection order corresponding to each task order according to collection order group parameters and each task order, so as to allocate picking tasks according to the collection order and the task order.

[0130] According to the technical solution of this embodiment of the invention, the task allocation management method first obtains the item identifiers of multiple orders and groups the item identifiers according to preset rules; then, it groups each group according to task order grouping parameters to obtain task orders; finally, it groups each task order according to set order grouping parameters to obtain set orders, thereby realizing task allocation management. This method is applicable to the formation of task orders and set orders in various business scenarios, decoupling the formation logic of task orders and set orders. It uses a splitting algorithm for order grouping, adjusts for extreme data, improves the saturation of task orders and set orders, reduces labor costs, and improves picking efficiency. Moreover, this method is universal, has low development difficulty and cost, and is easy to implement.

[0131] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for managing task allocation, characterized in that, include: Retrieve the item identifiers from multiple orders; The corresponding pile for each item identifier is determined according to preset rules; The task order corresponding to each sub-stack is determined based on the single parameter of the task order group and each sub-stack. Based on the parameters of the collection order and each task order, determine the collection order corresponding to each task order, and allocate picking tasks according to the collection order and the task order.

2. The method according to claim 1, characterized in that, The task order group has multiple single parameters; the task order corresponding to each sub-stack is determined based on the single parameters of the task order group and each sub-stack, including: Retrieve the group single parameter value corresponding to each task group single parameter in each sub-heap; Based on the single parameter values ​​of each group and the upper limit threshold of the single parameter of each task group, the single parameter of the target group of the task is determined from the single parameters of multiple task groups. Based on the task order target grouping parameters, group each sub-stack into tasks and determine the task order corresponding to each sub-stack.

3. The method according to claim 1, characterized in that, The set of single parameters may be multiple. The set of single parameters and each task order are used to determine the set corresponding to each task order, including: Retrieve the group parameter value corresponding to each set of group parameters in each task order; Based on the single parameter values ​​of each group and the upper limit threshold of the single parameter of each set, the single parameter of the target group is determined from multiple single parameters of sets; Based on the set target group parameters, each task order is grouped into a set, and the set corresponding to each task order is determined.

4. The method according to claim 2, characterized in that, Based on the task order target grouping parameters, group each sub-stack into tasks, and determine the task order corresponding to each sub-stack, including: Obtain the identifiers of each item in the pile; Obtain the target group single parameter value corresponding to the target group single parameter of the task order for each item identifier in the pile; Based on the single parameter values ​​of each target group and the upper limit threshold of the single parameter of the target group of the task order, the task order corresponding to each item identifier in the pile is determined, so as to determine the task order corresponding to the pile.

5. The method according to claim 4, characterized in that, Determining the task order corresponding to each item identifier in the pile includes: Identify the first item in the pile whose single parameter value of the target group is greater than or equal to the upper threshold. Based on the single parameter value of the target group and the upper limit threshold, one or more task orders corresponding to the first item identifier are determined.

6. The method according to claim 5, characterized in that, Determining the task order corresponding to each item identifier in the pile also includes: Identify the identifiers of each second item in the pile whose single parameter value of the target group is less than the upper threshold. Each second item identifier is treated as an array, and the arrays are sorted according to the single parameter value of the target group in each array; Based on the sorting results, determine the task order corresponding to each array, and then determine the task order corresponding to each of the second item identifiers.

7. The method according to claim 6, characterized in that, The sorting result is that each array is sorted in ascending order according to the single parameter value of the target group; the task sheet corresponding to each array is determined based on the sorting result, including: Calculate the sum of the target group single parameter values ​​of the first n arrays in the sorting. If the calculation result is greater than the upper limit threshold, divide the first n-1 arrays into a group to obtain each group. The sum of the target group single parameter values ​​of each array in each group is taken as the target group single parameter value of the group. Wherein, n is a natural number greater than 1. Determine the distance between each of the other groups (excluding the first group) and the upper limit threshold, and sort the other groups in ascending order of distance; Based on the group single parameter value of each of the other sorted groups, the group single parameter value of each array in the first group, and the upper limit threshold, the first group is split to obtain the updated groups. The task sheet corresponding to each array is determined based on the updated groupings.

8. A task allocation management device, characterized in that, include: The module retrieves the identifiers of each item from multiple orders. The first determination module determines the corresponding pile for each item identifier according to preset rules; The second determination module determines the task order corresponding to each sub-stack based on the single parameters of the task order group and each sub-stack. The third determining module determines the collection order corresponding to each task order based on the collection order parameters and each task order, so as to allocate picking tasks according to the collection order and the task order.

9. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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