Method for creating wave, electronic device and storage medium

Abstract

The invention relates to a wave creation method, electronic equipment and a storage medium, and is applied to the technical field of computers.The method comprises the steps that cargo storage information of a plurality of orders to be picked in a target storage site is obtained, and the cargo storage information comprises first roadway information of a current roadway, the current roadway is a roadway where to-be-picked goods are located in the to-be-picked order; determining a roadway score of each to-be-picked order on each roadway based on the first roadway information; determining a target roadway with the highest order concentration degree based on the roadway score; based on the roadway scores of the multiple orders to be picked in the target roadway, at least one target picking order is determined in the multiple orders to be picked, the wave order is created, the roadway score corresponding to the at least one target picking order meets a preset screening condition, and the wave order is created according to the roadway score corresponding to the at least one target picking order. The preset screening condition comprises at least one of the following conditions: the roadway score is greater than a preset score threshold, and the roadway score is one of the previous preset number with the highest roadway score ranking.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202511130659.3 (22) Application Date 2025.08.12 (71) Applicant SF Technology Co., Ltd. Address 518000, 6th-13th Floor, Block B, Building 1, Software Industry Base, Intersection of Xuefu Road (South) and Baishi Road (East), Nanshan District, Shenzhen, Guangdong Province (72) Inventors Zou Xihao, Liu Yao (74) Patent Agency Beijing Brui Intellectual Property Agency Co., Ltd. 11505 Patent Attorney Shang Wenwen (51) Int.Cl. G06Q 10 / 0631 (2023.01) G06Q 10 / 083 (2024.01) G06Q 30 / 0601 (2023.01) (54) Invention Title: Method, Electronic Device, and Storage Medium for Creating Waves (57) Abstract: This application relates to a method, electronic device, and storage medium for creating waves, applied in the field of computer technology. The method includes: acquiring cargo storage information of multiple pending-pick orders under a target storage area, the cargo storage information including first lane information of the current lane, the current lane being the lane where the pending-pick goods are located in the pending-pick orders; determining the lane score of each pending-pick order in each lane based on the first lane information; determining the target lane with the highest order concentration based on the lane score; determining at least one target picking order among the multiple pending-pick orders and creating a wave based on the lane scores of the multiple pending-pick orders in the target lane, wherein the lane score corresponding to at least one target picking order satisfies a preset screening condition, wherein the preset screening condition includes at least one of the following: the lane score is greater than a preset score threshold, and the lane score is one of the top preset quantities with the highest lane score ranking. Claims 3 pages, Description 16 pages, Drawings 4 pages, CN 121235306 A 2025.12.30 CN 1 21 23 53 06 A 1. A wave creation method, characterized in that the method is applied to wave creation of picking orders for a target storage area, the target storage area comprising multiple lanes, comprising: acquiring cargo storage information of multiple picking orders under the target storage area, the cargo storage information including first lane information of the current lane, the current lane being the lane where the picking cargo in the picking order is located; determining the lane score of each picking order on each lane based on the first lane information, the lane score indicating the degree of concentration dependence of the picking path of the picking order on each lane; determining the target lane with the highest order concentration based on the lane score; Based on the lane scores of the multiple pending picking orders in the target lane, at least one target picking order is determined from the multiple pending picking orders and a wave is created, wherein the lane score corresponding to the at least one target picking order is...1. The method according to claim 1, wherein determining the lane score of each order to be picked based on the first lane information includes: obtaining the total lane score of all lanes in the target storage area; determining the covered lanes in the lanes based on the first lane information, wherein the covered lanes are lanes covered by the picking path when picking the order to be picked; determining the first lane score of the covered lanes based on the second lane information of the covered lanes and the total lane score; determining the second lane score of other lanes based on the positional relationship between other lanes and the covered lanes and the first lane score, wherein the other lanes are lanes in the target storage area other than the covered lanes; determining the first lane score and the second lane score as the lane score. 3. The method according to claim 2, wherein the first lane information includes the location information of the current lane in the target storage area; determining the covered lanes in the lanes based on the first lane information includes: when the number of current lanes is 1, determining the current lane as the covered lane; when the number of current lanes is two or more, determining the two farthest boundary lanes in the current lanes according to the location information; determining the boundary lanes and the lanes between the boundary lanes as the covered lanes. 4. The method according to claim 2, wherein the second lane information includes the lane score of each covered lane, and determining the first lane score of the covered lanes based on the second lane information of the covered lanes and the total lane score includes: calculating a first sum of the lane scores of each covered lane; determining the difference between the total lane score and the first sum as the first lane score. 5. The method according to claim 2, characterized in that determining the second lane score of other lanes based on the positional relationship between other lanes and the covered lane and the score of the first lane includes: configuring the second lane scores of other lanes to decrease sequentially according to the positional relationship and in order of proximity to the covered lane, wherein the second lane score is less than the first lane score. 6. The method according to claim 1, characterized in that determining the target lane with the highest order concentration based on the lane score includes: determining the total lane score of each lane based on the lane scores of each order to be picked in each lane; determining the target lane from the lanes based on the total lane score.7. The method according to claim 6, wherein determining the target lane from the lanes based on the total lane score comprises: determining a first maximum value among the total lane scores; if there is only one first maximum value, determining the lane corresponding to the first maximum value as the target lane; if there are two or more first maximum values, calculating a second sum of the total lane score of the first adjacent lanes adjacent to the candidate lane and the first maximum value, wherein the candidate lane is the lane corresponding to the first maximum value; and determining the target lane based on the second sum. 8. The method according to claim 7, wherein determining the target lane based on the second sum comprises: determining a second maximum value among the second sum; if there are two or more second maximum values, increasing the number of the first adjacent lanes and determining the second maximum value again; if there is only one second maximum value, determining the candidate lane corresponding to the second maximum value as the target lane. 9. The method according to claim 1, characterized in that, when the preset screening condition includes one of the top preset number of lane scores with the highest lane score ranking, the step of determining at least one target picking order and creating a wave based on the lane scores of the multiple pending picking orders in the target lane includes: sorting the multiple pending picking orders based on the lane scores of the pending picking orders in the target lane; determining the lane distribution of the previous pending picking order when there are at least two similar pending picking orders, wherein the similar pending picking orders are pending picking orders with the same lane score, and the previous pending picking order is the pending picking order that ranks before and is closest to the target pending picking order; calculating the extended score of each similar pending picking order based on the lane distribution; sorting the similar pending picking orders with the same lane score according to the extended score to obtain the sorting result of the multiple pending picking orders; determining the top preset number of pending picking orders with the highest ranking in the sorting result as the target picking order and creating a wave. 10. The method according to claim 9, characterized in that determining the lane distribution of the previous picking order includes: calculating a third sum of lane scores for the target lane and a second adjacent lane adjacent to one side; calculating a fourth sum of lane scores for the target lane and a third adjacent lane adjacent to the other side; determining a target sum between the third sum and the fourth sum; and determining that the lane distribution is such that the lanes are distributed on one side of the adjacent lanes corresponding to the target sum. 11. The method according to claim 9, characterized in that, based on the lane distribution, calculating the extended score for each of the same claim 2 / 3 pages 3 CN 121235306 Class A picking orders includes:Based on the distribution of the lanes, the extension lanes extending in the direction of the target lane are determined; the sum of the lane scores of the extension lanes and the target lanes is determined as the extension score. 12. An electronic device, characterized in that it includes a memory and a processor; the memory is connected to the processor and is used to store a program; the processor is used to implement the wave creation method as described in any one of claims 1 to 11 by running the program in the memory. 13. A storage medium, characterized in that a computer program is stored on the storage medium, and the computer program is run by the processor to implement the wave creation method as described in any one of claims 1 to 11. Claims 3 / 3 Page 4 CN 121235306 A Wave creation method, electronic device and storage medium Technical field

[0001] This application relates to the field of logistics and warehousing technology, and particularly to a wave creation method, electronic device and storage medium. Background Art

[0002] Goods route optimization is the core link of warehousing and logistics, which directly affects operational efficiency and cost. Traditional manual wave creation suffers from problems such as repetitive paths and low efficiency, while the explosive growth of e-commerce has placed higher demands on warehouse response speed. According to statistics, the walking time for wave creation accounts for more than 50% of the total operation time. Therefore, optimizing paths through algorithms and dynamically adjusting order allocation has become the key to improving efficiency.

[0003] In related technologies, the integrated application of warehouse management systems is used. The warehouse management system randomly combines multiple orders into waves. However, the goods in the orders are often located in different aisles. The random wave creation method causes the picking objects to shuttle back and forth between aisles during picking, resulting in a long picking path and affecting picking efficiency. Summary of the Invention

[0004] This application provides a wave creation method, electronic device and storage medium to solve the problem of long picking paths affecting picking efficiency in the prior art.

[0005] According to a first aspect of the embodiments of this application, a wave creation method is provided, the method being applied to wave creation of picking orders for a target storage area, the target storage area comprising multiple lanes, comprising:

[0006] obtaining cargo storage information of multiple picking orders under the target storage area, the cargo storage information including first lane information of the current lane, the current lane being the lane where the picking goods in the picking orders are located;

[0007] determining the lane score of each picking order on each lane based on the first lane information, the lane score indicating the degree of concentration dependence of the picking path of the picking orders on each lane;

[0008] determining the target lane with the highest order concentration based on the lane score;

[0009] determining the target lane with the highest order concentration based on the lane score of the multiple picking orders in the target lane;In the process, at least one target picking order is identified and a wave is created, wherein the lane score corresponding to the at least one target picking order meets a preset screening condition, wherein the preset screening condition includes at least one of the following: the lane score is greater than a preset score threshold, and the lane score is one of the top preset number of lanes with the highest ranking.

[0010] Optionally, determining the lane score of each order to be picked in each lane based on the first lane information includes:

[0011] obtaining the total lane score of all lanes in the target storage area;

[0012] determining the covered lanes in the lanes based on the first lane information, wherein the covered lanes are the lanes covered by the picking path when picking the order to be picked;

[0013] determining the first lane score of the covered lanes according to the second lane information of the covered lanes and the total lane score;

[0014] determining the second lane score of other lanes according to the positional relationship between other lanes and the covered lanes and the first lane score, wherein the other lanes are the lanes in the target storage area other than the covered lanes; Specification 1 / 16 page 5 CN 121235306 A

[0015] determining the first lane score and the second lane score as the lane score.

[0016] Optionally, the first lane information includes the location information of the current lane in the target storage area;

[0017] Determining the covered lanes in the lanes based on the first lane information includes:

[0018] When the number of current lanes is 1, determining the current lane as the covered lane;

[0019] When the number of current lanes is two or more, determining the two boundary lanes that are farthest apart in the current lanes according to the location information;

[0020] Determining the boundary lanes and the lanes between the boundary lanes as the covered lanes.

[0021] Optionally, the second lane information includes the lane score of each covered lane, and determining the first lane score of the covered lanes according to the second lane information of the covered lanes and the total lane score includes:

[0022] Calculating the first sum of the lane scores of each covered lane;

[0023] Determining the difference between the total lane score and the first sum as the first lane score.

[0024] Optionally, determining the second lane score of other lanes based on the positional relationship between other lanes and the covered lane and the score of the first lane includes:

[0025] Based on the positional relationship, configuring the second lane scores of other lanes to decrease sequentially according to their proximity to the covered lane, wherein the second lane score is less than the first lane score.

[0026] Optionally, determining the target lane with the highest order concentration based on the lane score includes:

[0027] Based on the lane scores of each of the picking orders in each of the lanes, determine the total lane score for each lane;

[0028] Determine the target lane from the lanes based on the total lane score.

[0029] Optionally, determining the target lane from the lanes based on the total lane score includes:

[0030] Determining a first maximum value among the total lane scores;

[0031] If there is only one first maximum value, determine the lane corresponding to the first maximum value as the target lane;

[0032] If there are two or more first maximum values, calculate a second sum of the total lane score of the first adjacent lane adjacent to the candidate lane and the first maximum value, wherein the candidate lane is the lane corresponding to the first maximum value;

[0033] Determine the target lane based on the second sum.

[0034] Optionally, determining the target lane based on the second sum includes:

[0035] determining the second maximum value among the second sums;

[0036] if there are two or more second maximum values, increasing the number of the first adjacent lanes and determining the second maximum value again;

[0037] if there is only one second maximum value, determining the candidate lane corresponding to the second maximum value as the target lane.

[0038] Optionally, when the preset filtering conditions include the case that the lane score is one of the top preset number of lane scores with the highest ranking, the step of determining at least one target picking order and creating a wave based on the lane scores of the multiple pending picking orders in the target lane includes:

[0039] sorting the multiple pending picking orders based on the lane scores of the pending picking orders in the target lane;

[0040] when there are at least two similar pending picking orders, determining the lane distribution of the previous pending picking order, wherein the similar pending picking orders are pending picking orders with the same lane score, and the previous pending picking order is the pending picking order that ranks before and is closest to the target pending picking order on page 2 / 16 of the specification, CN 121235306 A;

[0041] calculating the extended score of each of the similar pending picking orders based on the lane distribution;

[0042] According to the extended score, sort the same type of pending orders with the same lane score to obtain the sorting result of the multiple pending orders;

[0043] Determine the top preset number of pending orders with the highest ranking in the sorting result as the target pending orders and create a wave.

[0044] Optionally, determining the lane distribution of the previous pending order includes:

[0045] Calculating the third sum of lane scores of the target lane and the second adjacent lane adjacent to one side;

[0046] Calculating the fourth sum of lane scores of the target lane and the third adjacent lane adjacent to the other side;

[0047] Determine the larger target sum between the third sum and the fourth sum;

[0048] Determine the lane distribution as the lanes being distributed on one side of the adjacent lanes corresponding to the target sum.

[0049] Optionally, based on the lane distribution, calculate the extension score for each of the same type of order to be picked, including:

[0050] Determine the extension lanes in the direction of the target lane extension based on the lane distribution;

[0051] Determine the sum of the lane scores of the extension lanes and the target lanes as the extension score. According to a second aspect of the embodiments of this application, a wave creation apparatus is provided, comprising:

[0052] an acquisition unit, configured to acquire cargo storage information of multiple pending-picking orders under a target storage area, the cargo storage information including first lane information of the current lane, wherein the current lane is the lane where the pending-picking goods in the pending-picking orders are located;

[0053] a first determination unit, configured to determine the lane score of each pending-picking order on each lane based on the first lane information, wherein the lane score indicates the degree of concentration dependence of the picking path of the pending-picking order on each lane;

[0054] a second determination unit, configured to determine the target lane with the highest order concentration based on the lane score;

[0055] A creation unit is configured to determine at least one target picking order and create a wave based on the wave score of the plurality of picking orders in the target aisle, wherein the wave score corresponding to the at least one target picking order satisfies a preset filtering condition, wherein the preset filtering condition includes at least one of the following: the wave score is greater than a preset score threshold, and the wave score is one of the top preset numbers of wave scores.

[0056] According to a third aspect of the present application, an electronic device is provided, including a memory and a processor;

[0057] The memory is connected to the processor and is used to store a program;

[0058] The processor is configured to implement the wave creation method as described in the first aspect by running the program in the memory.

[0059] According to a fourth aspect of the present application, a storage medium is provided, wherein a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the wave creation method as described in the first aspect.

[0060] According to a fifth aspect of the present application, a computer program product is provided, including computer program instructions, which, when executed by a processor, cause the processor to execute the wave creation method as described in the first aspect.

[0061] The technical solution provided in this application embodiment has the following advantages compared with the prior art: The method provided in this application embodiment obtains the cargo storage information of multiple pending orders under the target storage site, cargo storage information specification 3 / 16 pages 7 CNThe information includes the first lane information of the current lane, which is the lane where the goods to be picked in the order to be picked are located; based on the first lane information, the lane score of each order to be picked is determined in each lane, the lane score indicating the degree of concentration dependence of the picking path of the order to be picked on each lane; based on the lane score, the target lane with the highest order concentration is determined; based on the lane scores of the multiple orders to be picked in the target lane, at least one target picking order is determined among the multiple orders to be picked and a wave is created, wherein the lane score corresponding to the at least one target picking order meets the preset screening conditions, wherein the preset screening conditions include at least one of the following: the lane score is greater than the preset score threshold, and the lane score is one of the top preset number of lane scores with the highest ranking. Thus, based on the lane score indicating the degree of concentration dependence of the picking path of the order to be picked on each lane, the target lane with the highest order concentration is determined. Furthermore, according to the lane score on the target lane, the order to be picked in the wave is determined, which allows the goods to be picked in the order to be picked in the wave to be concentrated near the target lane, making the picking range more concentrated, shortening the picking path, and thus improving picking efficiency.

[0062] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0063] Figure 1 is a flowchart of a wave creation method provided in an embodiment of this application;

[0064] Figure 2 is an overall architecture diagram of a wave creation method provided in an embodiment of this application;

[0065] Figure 3 is a flowchart of a wave creation method provided in another embodiment of this application;

[0066] Figure 4 is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Description

[0067] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0068] Exemplary Implementation Environment

[0069] The wave creation method according to the embodiments of this application can be executed by electronic devices such as terminal devices or servers. The terminal device can be user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA).Assistant (PDA), handheld devices, computing devices, vehicle-mounted devices, wearable devices, etc., the server can be an independent physical server, a server cluster composed of multiple physical servers, or a cloud server capable of cloud computing. This method can be implemented by the processor calling computer-readable program instructions stored in the memory. This application uses the wave creation method executed by the server as an example for explanation, but does not limit it.

[0070] Exemplary Method

[0071] Before describing the embodiments of the present invention in detail, the relevant background involved in the embodiments of the present invention will be further explained.

[0072] Warehouse Management System (WMS) is used to manage the daily operations of the warehouse, including inventory management, order processing, goods storage and retrieval, etc. It can improve warehouse operation efficiency, reduce errors, optimize inventory levels, and support real-time data tracking and reporting.

[0073] Order Pool: For uncreated wave orders, a kind of shallow processing data is used to calculate the order structure, and then the number of orders with the same structure is counted. Its application scenario includes combining orders with the same structure as much as possible when performing wave grouping logic calculation to improve picking efficiency.

[0074] Batch: Refers to combining multiple orders, tasks, or goods into a "batch" according to specific rules, improving warehouse operation efficiency through centralized processing. Its essence is the "batch integration" of scattered operations, commonly seen in picking, replenishment, and shipping, especially effective when order volume is large or complex.

[0075] Aisle: The passageway inside the warehouse used for storing and transporting goods. It is an important component of the warehouse layout, directly affecting warehouse operating efficiency and space utilization.

[0076] StarRock: A high-performance distributed SQL database designed for real-time analysis and large-scale data processing. Supports high-concurrency queries, low latency, easy expansion, and compatibility with the MySQL protocol.

[0077] Flink: An open-source stream processing framework for handling unbounded and bounded data streams. Application scenarios: real-time data analysis, event-driven applications, complex event processing, data pipelines, etc. High throughput, low latency, precise one-time processing semantics, supports state management and fault tolerance.

[0078] MySQL: An open-source relational database management system that uses Structured Query Language (SQL) for database management. It supports multiple users and multiple threads, and has good performance, reliability and ease of use.

[0079] Redis: An open-source in-memory data structure store used as a database, cache and message queue. Its data structures support strings, hashes, lists, sets, sorted sets, etc. Application scenarios include cache acceleration, session storage, leaderboards, message queues, etc. It features high performance, persistence, master-slave replication, transaction support, Lua scripting, etc.

[0080] Normal Wave: A wave consisting of orders with sufficient capacity, not yet close to the end of the workday, and not yet due for delivery is called a normal wave. Normal waves are always prioritized for total order fulfillment; if insufficient, orders will be held back.

[0081] Emergency Wave: In contrast to normal waves, an emergency wave consists of orders with insufficient capacity, close to the end of the workday, and due for delivery. Emergency waves are created as much as possible to fulfill total order fulfillment; if conditions are not met, orders will not be held back, but mixed waves will be created, prioritizing fulfilling delivery deadlines.

[0082] Single Item: An order containing only one item.

[0083] Multiple Items: An order containing more than one item.

[0084] Mixed Wave: A wave created when the number of orders with the same structure does not reach a certain threshold (wave rule configuration). Prioritizes fulfilling delivery deadlines and has low requirements for picking efficiency.

[0085] Total Order Fulfillment Wave: A wave created when the number of orders with the same structure reaches a certain threshold (wave rule configuration). Prioritizes fulfilling picking efficiency and has low requirements for delivery deadlines.

[0086] Please refer to Figure 1. In an exemplary embodiment, a wave creation method is provided. The method is applied to create waves of picking orders for a target storage area, which includes multiple lanes, including:

[0087] Step 101: Obtain the cargo storage information of multiple picking orders under the target storage area. The cargo storage information includes the first lane information of the current lane, where the current lane is the lane where the goods to be picked in the picking order are located.

[0088] In some embodiments, the picking order can be an order in an order pool. The cargo storage information of each picking order includes the first lane information of the lane where the goods to be picked are located. The first lane information may include the location of the current lane in the target storage area and the target lane identifier (e.g., lane number).

[0089] Typically, there are multiple lanes in a target storage area, and each lane has its own lane identifier. Goods to be picked are stored in each aisle. Therefore, the current aisle corresponding to page 5 / 16 of the instruction manual, CN 121235306 A, can be determined through the goods to be picked in the goods storage information of the order to be picked.

[0090] The above-mentioned goods storage information can be obtained through the warehouse management system and IoT devices (such as RFID tags, sensors, etc.), which includes multi-dimensional data such as real-time collection of order information, inventory information, first aisle information, and equipment status information. Goods storage information includes order number, order creation time, customer information, product information, first aisle information, etc.; inventory information includes the quantity, location, and shelf life of the products; first aisle information includes aisle number, length, width, and goods storage status, etc. This information is recorded in the mysql database of the WMS system. The Chuangbo algorithm obtains the business data (orders, storage locations, inventory, products, etc.) required by the Chuangbo algorithm by listening to the mysql binlog log and synchronizes it to starRocks.Database. Does not affect business systems, real-time performance at the second level.

[0091] Data preprocessing: WMS cleans, transforms, and integrates the collected data, removing noise and duplicate data, unifying data formats, and integrating data from different sources into a data warehouse. For example, standardizing the first lane information in the goods storage information ensures data consistency and accuracy; real-time updating of inventory information ensures data timeliness.

[0092] Step 102: Based on the first lane information, determine the lane score of each order to be picked on each lane. The lane score indicates the degree of central dependence of the picking path of the order to be picked on each lane.

[0093] In some embodiments, the first lane information includes a target lane identifier. Based on the target lane identifier, it is possible to determine the lanes that need to be traversed on the picking path when picking the goods to be picked in the order to be picked. By determining the lane score, the picking efficiency of the order to be picked can be indicated. That is, the higher the lane score, the fewer lanes need to be crossed when picking the order to be shipped, and the more concentrated the lanes are, thus the higher the picking efficiency. The lower the lane score, the more lanes need to be crossed when picking the order to be shipped, and the more dispersed the lanes are, thus the lower the picking efficiency.

[0094] In an optional embodiment, determining the lane score of each order to be picked on each lane based on the first lane information includes:

[0095] obtaining the total lane score of all lanes in the target storage area;

[0096] determining the covered lanes in the lanes based on the first lane information, wherein the covered lanes are the lanes covered by the picking path when picking the order to be picked;

[0097] determining the first lane score of the covered lanes based on the second lane information of the covered lanes and the total lane score;

[0098] determining the second lane score of other lanes based on the positional relationship between other lanes and the covered lanes and the first lane score, wherein the other lanes are the lanes in the target storage area other than the covered lanes;

[0099] determining the first lane score and the second lane score as the lane score.

[0100] In some embodiments, the set of lanes configured in the target storage area can be represented as A = {A1, A2, ..., An}, and the lane score of each lane is di (i represents the lane number), so the total lane score S_total is S_total = Σ di (i ∈ all lane numbers).

[0101] The lane score mentioned above indicates the distance coefficient of the lane. The distance coefficient of the lane can be set based on the actual situation. For example, it can be converted according to the actual measured distance of each lane in the warehouse. If there is no actual measured distance, it can be configured according to a preset value. The distance coefficients of each lane can be the same or different. For example, the distance coefficients can be...All are set to 1. The total lane score is the sum of the lane scores of all lanes in the target storage area.

[0102] Based on the first lane information of the current lane in the order to be picked, the lanes that need to be crossed when picking the order to be picked can be determined, that is, the lanes covered from the current lane at one end to the current lane at the other end (i.e., the covered lanes) need to be determined. Then, the first lane score is determined based on the second lane information of the covered lanes. Specification 6 / 16 pages 10 CN 121235306 A

[0103] Wherein, the higher the first lane score, the fewer lanes covered by the order to be picked when picking the order to be picked in the target storage area, the fewer lanes that need to be crossed, and the higher the picking efficiency. Since other lanes do not contain the goods to be picked, the second lane score configured for other lanes is lower than the first lane score. For example, the second lane score can be configured in descending order of distance between other lanes and the boundary lanes, i.e., the closer other lanes are to the boundary lanes, the higher their second lane score.

[0104] In an optional embodiment, the first lane information includes the location information of the current lane in the target storage area;

[0105] Determining the coverage lanes to be crossed when picking the order to be picked based on the first lane information includes:

[0106] When the number of current lanes is 1, determining the current lane as the coverage lane;

[0107] When the number of current lanes is two or more, determining the two boundary lanes that are farthest apart among the current lanes according to the location information; determining the boundary lanes and the lanes between the boundary lanes as the coverage lanes.

[0108] In some embodiments, when there is only one current lane in the order to be picked that includes the goods to be picked, it means that the order to be picked covers only one lane. The score of the first lane is determined as the difference between the total lane score and the lane score of the current lane, which can be expressed as: the first lane score S_order = S_total - Σ dj (j∈ the lane number covered by the order to be picked). In this example, j is the lane number of the current lane.

[0109] For example, if the current lane is lane A3, the total lane score is 10, and the lane score of lane A3 is 2, then the first lane score of lane A3 is 10 - 2 = 8.

[0110] When there is more than one current lane in the order to be picked that includes the goods to be picked, it means that the order to be picked covers multiple lanes. When picking, more than two lanes need to be crossed. Therefore, it is necessary to first determine the lane situation covered by the order to be picked. Specifically, based on the current location information of the tunnel, the two farthest boundary tunnels are first determined. Then, the boundary tunnels and the tunnels between the boundary tunnels are determined as the covered tunnels.

[0111] In one optional embodiment, the second lane information includes lane scores for each of the covered lanes. Determining a first lane score for each covered lane based on the second lane information and the total lane score includes:

[0112] calculating a first sum of the lane scores for each of the covered lanes;

[0113] determining the difference between the total lane score and the first sum as the first lane score.

[0114] In some embodiments, the lane scores of each covered lane are added together to obtain a first sum indicating the length of the picking path when picking an order. The larger the first sum, the longer the picking path. The first lane score, obtained by calculating the difference between the total lane score and the first sum, indicates the length of the distance that does not need to be walked during picking. The higher the first lane score, the shorter the distance that does not need to be walked, thus increasing picking efficiency.

[0115] Typically, the number of orders to be picked in the order pool is large. For ease of understanding, in this embodiment, we take an example where there are 7 orders to be picked, 9 aisles in the target storage area, aisle numbers from 1 to 9, and a distance coefficient of 1 for each aisle (i.e., a total of 9 aisles). See Table 1 below. Taking order 001 as an example, its current aisles are aisles A3 and A4 (i.e., the cells with circles in Table 1).

[0116] Table 1

[0117] Order No. A-1 A-2 A-3 A-4 A-5 A-6 A-7 A-8 A-9 001 OO Instruction Manual 7 / 16 Page 11 CN 121235306 A 002 0 003 OO 004 OO 005 OO 006 0OO 007 0OO

[0118] As shown in Table 1 above, taking order 006 to be picked as an example, the current lanes are A2, A3 and A6. According to the distance between the three, A2 and A6 are the farthest apart. Therefore, A2 and A6 are the boundary lanes. The lanes between them are A3, A4 and A5. That is, the covered lanes are A2, A3, A4, A5 and A6. Therefore, the score of the first lane of the covered lanes A2, A3, A4, A5 and A6 is 9-(2+3) = 4.

[0119] Taking order 002 to be picked as an example, the current lane is A4. Since its current lane is 1 and the covered lane is A4, its first lane score can be directly calculated as 9-1, which is 8.

[0120] After determining the first lane score of the current lane for each order to be picked, the following Table 2 can be obtained.

[0121] Table 2

[0122]

[0123]

[0124] In an optional embodiment, the second lane score of other lanes is determined according to the positional relationship between other lanes and the covered lane and the first lane score, including:

[0125] According to the positional relationship, the second lane scores of other lanes are determined in order from closest to furthest from the covered lane.The lane scores are configured to decrease sequentially, with the second lane score being less than the first lane score. The other lanes are the lanes in the target storage area other than the covered lanes.

[0126] In some embodiments, based on the example in Table 1 above, after obtaining the first lane score, the other lanes can be set to lower lane scores. The higher the lane score, the smaller the contribution of the lane to the order picking distance, that is, the higher the picking efficiency on the lane.

[0127] Based on Table 1 above, taking order 006 to be picked as an example, the first lane score of A2, A3, A4, A5 and A6 is 4. Therefore, for the other lanes, the lane scores are set to decrease sequentially, that is, the second lane score of A1 is 3, and the second lane scores of A7, A8 and A9 are 3, 2 and 1 respectively. This leads to the following Table 3.

[0128] Table 3

[0129] Order No. A-1 A-2 A-3 A-4 A-5 A-6 A-7 A-8 A-9 001 5 6 7 7 6 5 4 3 2 002 5 6 7 8 7 6 5 4 3 003 0 0 0 0 0 0 0 0 004 1 2 3 4 5 6 6 6 5 Instruction Manual 8 / 16 Page 12 CN 121235306 A 005 5 5 5 5 4 3 2 1 0 006 3 4 4 4 4 4 4 3 2 1 007 4 5 6 6 6 5 4 3 2

[0130] Step 103: Determine the target lane with the highest order concentration based on the lane score.

[0131] In an optional embodiment, determining the target lane with the highest order concentration based on the lane score includes:

[0132] determining the total lane score of each lane based on the lane score of each order to be picked in the lane;

[0133] determining the target lane from the lanes based on the total lane score.

[0134] In some embodiments, after obtaining the lane score of each order to be picked in each lane, the lane scores of each order to be picked in the lane can be added together to obtain the total lane score.

[0135] Based on the above embodiments, as shown in Table 3, for storage lane A1, its total lane score is 5+5+0+1+5+3+4, which is 23. Similarly, the total lane score of each lane is obtained, as shown in Table 4 below. Table 4 Order Number A‑1 A‑2 A‑3 A‑4 A‑5 A‑6 A‑7 A‑8 A‑9 001 5 6 7 7 6 5 4 3 2 002 5 6 7 8 7 6 5 4 3 003 0 0 0 0 0 0 0 0 0 004 1 2 3 4 5 6 6 6 5 005 5 5 5 5 4 3 2 1 0 0063 4 4 4 4 4 3 2 1 007 4 5 6 6 6 5 4 3 2 Total 23 28 32 34 32 29 24 19 13

[0138] In an optional embodiment, determining the target lane from the lanes based on the total lane score includes:

[0139] Determining a first maximum value in the total lane score;

[0140] If there is only one first maximum value, determining the lane corresponding to the first maximum value as the target lane;

[0141] If there are two or more first maximum values, calculating a second sum of the total lane score of the first adjacent lane adjacent to the candidate lane and the first maximum value, wherein the candidate lane is the lane corresponding to the first maximum value;

[0142] Determining the target lane based on the second sum.

[0143] In some embodiments, as shown in the examples provided in Table 4, by comparing the nine lanes, the maximum total lane score is lane A4, and there is only one first maximum value; therefore, lane A4 is determined as the target lane.

[0144] In another embodiment, as shown in the examples provided in Table 5, by comparing the nine lanes, the maximum total lane score is 19, and there are two, namely lanes A4 and A5. In this case, it is necessary to select one of them as the target lane.

[0145] The adjacent lanes of A4 are A3 and A5, and the adjacent lanes of A5 are A4 and A6. Therefore, the second sum value corresponding to A4 is determined to be: SUM(A3,A4,A5) = 56, and the second sum value corresponding to A5 is: SUM(A4,A5,A6) = 56.

[0146] Table 5

[0147] Order No. A-1 A-2 A-3 A-4 A-5 A-6 A-7 A-8 A-9 Instruction Manual 9 / 16 Page 13 CN 121235306 A 007 4 5 6 6 6 5 4 3 2 005 5 5 5 5 4 3 2 1 0 006 3 4 4 4 4 4 4 3 2 1 004 1 2 3 4 5 6 6 6 5 003 0 0 0 0 0 0 0 0 0 Total 13 16 18 19 19 18 15 12 8

[0148] In an optional embodiment, determining the target tunnel based on the second sum includes:

[0149] Determining the second maximum value in the second sum;

[0150] If there are two or more second maximum values, the number of the first adjacent lanes is increased, and the second maximum value is determined again;

[0151] If there is only one second maximum value, the candidate lane corresponding to the second maximum value is determined as the target lane.

[0152] In some embodiments, after calculating the second sum, the second maximum value is determined by comparison.If there is only one maximum value, then the candidate lane corresponding to the second maximum value is the target lane. For example, if the calculated second sum values ​​are 56 and 57 respectively, then the candidate lane corresponding to 57 is taken as the target lane.

[0153] Based on the example provided in Table 5 above, the second maximum value is 56, that is, there are more than two second maximum values. At this time, it is necessary to further diffuse from the candidate lane to the nearby lanes to obtain the second sum value corresponding to A4 as: SUM(A2,A3,A4,A5,A6)=90, and the second sum value corresponding to A5 as: SUM(A3,A4,A5,A6,A7)=89. There is a second maximum value of 90 among the two. Therefore, A4 is taken as the target lane.

[0154] Step 104: Based on the lane score of the multiple orders to be picked in the target lane, determine at least one target picking order among the multiple orders to be picked and create a wave.

[0155] Wherein, the lane score corresponding to the at least one target picking order satisfies a preset screening condition, wherein the preset screening condition includes at least one of the following: the lane score is greater than a preset score threshold, and the lane score is one of the top preset quantities of lane scores.

[0156] In some embodiments, the target picking orders for creating waves are determined according to the lane score on the target lane, which can concentrate the goods to be picked in the target picking orders in the wave near the target lane, making the picking range more concentrated, shortening the picking path, and thus improving picking efficiency.

[0157] In an optional embodiment, the preset screening condition includes, when the lane score is greater than a preset score threshold, obtaining the preset score threshold, comparing the lane score of the target lane with the preset score threshold, and determining the orders to be picked that are greater than the preset score threshold as target picking orders and creating waves.

[0158] The preset score threshold can be set based on the actual situation. For example, it can be set to a fixed value, or it can be selected based on the lane score of the target lane. For example, the Xth lane score (set based on the actual situation, for example, 10) with the highest score among all lane scores can be selected.

[0159] In an optional embodiment, the preset screening condition includes the case that the lane score is one of the top preset number of lane scores with the highest ranking. Based on the lane score of the multiple pending orders in the target lane, at least one target picking order is determined among the multiple pending orders and a wave is created, including:

[0160] Sorting the multiple pending orders based on the lane score of the pending orders in the target lane;

[0161] In the case of at least two similar pending orders, determining the lane distribution of the previous pending order.In addition, the similar pending orders are pending orders with the same lane score, and the previous pending order is the pending order that is closest to the target pending order;

[0162] Based on the lane distribution, calculate the extended score of each similar pending order;

[0163] Sort the similar pending orders with the same lane score according to the extended score to obtain the sorting result of the multiple pending orders;

[0164] Determine the top preset number of pending orders with the highest ranking in the sorting result as the target picking order and create a wave.

[0165] In some embodiments, the pending orders are sorted according to the lane score in the target lane from high to low. For example, as shown in Table 3 above, the lane score in lane A4 is sorted. When the lane scores are different, they are sorted in order from high to low. When the lane scores are the same, it is necessary to determine the sorting according to the lane distribution of the previous pending order to obtain the sorting result shown in Table 6 below.

[0166] Table 6

[0167]

[0168]

[0169] In Table 6, the lane scores of orders 004 and 006 are both 4, which means they are the same type of orders to be picked. Therefore, it is necessary to determine their order.

[0170] The distribution of the lanes of the previous order to be picked includes a left-leaning distribution and a right-leaning distribution. Based on the distribution, the extension direction corresponding to the distribution is selected, the extension score of the target order to be picked is calculated, and the orders to be picked are sorted from high to low according to the extension score.

[0171] In an optional embodiment, determining the lane distribution of the previous picking order includes:

[0172] calculating a third sum of lane scores for the target lane and a second adjacent lane adjacent to one side;

[0173] calculating a fourth sum of lane scores for the target lane and a third adjacent lane adjacent to the other side;

[0174] determining the larger of the third sum and the fourth sum as a target sum;

[0175] determining that the lane distribution is such that the lanes are distributed on one side of the adjacent lanes corresponding to the target sum.

[0176] In some embodiments, as shown in the examples provided in Table 6, the previous order to be picked is 005. The third sum of the lane scores of lane A4 and lane A3 to its left is SUM(A3,A4) = 5 + 5, which is 10. The fourth sum of the lane scores of lane A4 and lane A5 to its right is SUM(A4,A5) = 5 + 4, which is 9. The larger of the two is the third sum, which corresponds to the left side of lane A4. Therefore, the lane distribution is determined to be distributed to the left side of lane A4.

[0177] It is understood that if the calculated third sum and fourth sum are the same, the number of adjacent second and third adjacent lanes can be increased until the larger of the two is determined.

[0178] In an optional embodiment, based on the lane distribution, the extension score for each of the same type of picking orders is calculated, including:

[0179] determining the extension lanes in the direction of the target lane based on the lane distribution; Specification 11 / 16 pages 15 CN 121235306 A

[0180] determining the sum of the lane scores of the extension lanes and the target lanes as the extension score.

[0181] In some embodiments, based on the examples provided in Table 6 above, when the lane distribution is distributed on the left side of lane A4, the sum of the lane scores of the extension lanes to the left of order 004 and the target lane is calculated as SUM004(A4,A3) = 4 + 3 = 8, and the sum of the lane scores of the extension lanes to the left of order 006 and the target lanes is SUM006(A4,A3) = 4 + 4 = 8.

[0182] Furthermore, by comparing the extended scores of the two orders to be picked, order 006 is greater than 004, therefore, order 006 is placed before 004.

[0183] The wave creation method of this application breaks the traditional fixed rule wave grouping method and adopts an intelligent wave grouping strategy based on order lane information. By analyzing and mining the lane information involved in the order, orders involving the same or adjacent lanes are combined into a wave. This makes the orders in each wave more concentrated in lane distribution, reduces the frequent movement of picking personnel between different lanes, and thus shortens the picking path. For example, by using algorithms to analyze orders in real time, the wave grouping scheme is dynamically adjusted according to the lane correlation and order priority to ensure that the orders in each wave can efficiently complete the picking task.

[0184] Its overall architecture diagram is shown in Figure 2. Among them, StarRocks is a high-performance analytical data warehouse that supports efficient import of data from various real-time and offline data sources, and also supports direct analysis of data in various formats on the data lake. StarRocks features horizontal scalability, high availability, high reliability, and easy operation and maintenance. Flink is a distributed streaming data stream engine. Flink executes arbitrary streaming data programs in a data parallel and pipelined manner. Flink's pipeline runtime system can execute batch processing and streaming processing programs. In addition, Flink's runtime itself also supports the execution of iterative algorithms. SQL, the language used by MySQL, is the most commonly used standardized language for accessing databases. Due to its small size, high speed, and open source, MySQL can be chosen as the website database. Redis is a key-value storage system. Redis periodically writes updated data to disk or writes modification operations to an append record file, and on this basis, it implements master-slave synchronization.

[0185] The wave creation method of this application is shown in Figure 3. First, orders are retrieved from the order pool and then wave-grouped.The pre-processing logic includes inventory judgment and storage location judgment. The algorithm evaluates the concentration score of orders in each aisle in the order pool, finds the aisle with the highest score (i.e., the highest concentration), and then sorts and groups the orders according to their concentration score in that aisle. Orders that have not been grouped continue to be grouped according to the above logic until all orders are grouped.

[0186] The wave creation method of this application, through the intelligent wave grouping strategy based on order aisle information and the real-time dynamic picking path planning algorithm, can significantly shorten the picking path, reduce the movement distance of picking personnel and aisles, thereby improving picking efficiency. According to the actual use of relevant warehouses, after adopting the technical solution of this invention, the total number of picking aisles of the new algorithm is reduced by 238, an increase of 17%, the average number of aisles per wave is reduced by 3.4, an increase of 16%, and the proportion of picking waves in only one aisle of the new algorithm is increased from 3% to 22%, with a significant picking concentration effect.

[0187] This application significantly improves picking efficiency, reduces labor costs and equipment usage time, thereby reducing warehouse operating costs. According to actual usage calculations in relevant warehouses, after adopting the technical solution of the present invention, the average picking efficiency of warehouse personnel has been optimized from 84 pieces per hour to 117 pieces per hour, an improvement of 39%.

[0188] Exemplary Device

[0189] Correspondingly, this application embodiment also provides a wave creation device, including:

[0190] an acquisition unit, used to acquire cargo storage information of multiple orders to be picked under the target storage area, the cargo storage information including the first lane information of the current lane, the current lane being the lane where the goods to be picked in the order to be picked are located; Specification 12 / 16 pages 16 CN 121235306 A

[0191] a first determination unit, used to determine the lane score of each order to be picked on each lane based on the first lane information, the lane score indicating the degree of concentration dependence of the picking path of the order to be picked on each lane;

[0192] a second determination unit, used to determine the target lane with the highest order concentration based on the lane score;

[0193] A creation unit is configured to determine at least one target picking order and create a wave based on the wave score of the plurality of orders to be picked in the target aisle, wherein the wave score corresponding to the at least one target picking order satisfies a preset screening condition, wherein the preset screening condition includes at least one of the following: the wave score is greater than a preset score threshold, and the wave score is one of the top preset quantities of the highest-ranking wave scores.

[0194] The wave creation device provided in this embodiment belongs to the same application concept as the wave creation method provided in the above embodiments of this application, and can execute the method provided in any of the above embodiments of this application, and has the corresponding function of executing the method.The module and beneficial effects. Technical details not described in detail in this embodiment can be found in the specific processing content of the wave creation method provided in the above embodiments of this application, and will not be repeated here.

[0195] The functions implemented by each unit in the above wave creation device can be implemented by the same or different processors, and this embodiment of the application does not limit this.

[0196] It should be understood that each unit in the above device can be implemented in the form of processor calling software. For example, the device includes a processor, the processor is connected to a memory, the memory stores instructions, the processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of each unit of the device, wherein the processor can be a general-purpose processor, such as a CPU or microprocessor, and the memory can be the memory inside the device or the memory outside the device. Alternatively, the units in the device can be implemented in the form of hardware circuits. The functions of some or all units can be realized through the design of hardware circuits. The hardware circuit can be understood as one or more processors. For example, in one implementation, the hardware circuit is an ASIC. The functions of some or all units can be realized through the design of the logical relationship between the components in the circuit. In another implementation, the hardware circuit can be implemented by a PLD. Taking FPGA as an example, it can include a large number of logic gates. The connection relationship between the logic gates can be configured through a configuration file to realize the functions of some or all units. All units of the above device can be implemented entirely by the processor calling software, or entirely by hardware circuits, or partially by the processor calling software, with the remaining part implemented by hardware circuits.

[0197] In the embodiments of this application, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a CPU, microprocessor, GPU, or DSP. In another implementation, the processor can realize certain functions through the logical relationship of the hardware circuit. The logical relationship of the hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an ASIC or PLD, such as an FPGA. In reconfigurable hardware circuits, the process of a processor loading a configuration document and configuring the hardware circuit can be understood as the process of a processor loading instructions to implement the functions of some or all of the above units. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as an NPU, TPU, DPU, etc.

[0198] It can be seen that each unit in the above device can be one or more processors (or processing circuits) configured to implement the above methods, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0199] Furthermore, all or part of the units in the above devices can be integrated together, or they can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a System-on-Chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of each unit of the device. The type of the at least one processor may be different, such as CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.

[0200] Exemplary Electronic Device

[0201] Another embodiment of this application also proposes an electronic device, as shown in FIG4, which includes:

[0202] a memory 400 and a processor 410;

[0203] wherein the memory 400 is connected to the processor 410 and is used to store a program;

[0204] the processor 410 is used to implement the wave creation method disclosed in any of the above embodiments by running the program stored in the memory 400.

[0205] Specifically, the above-mentioned wave creation device may further include: a bus, a communication interface 420, an input device 430, and an output device 440.

[0206] The processor 410, memory 400, communication interface 420, input device 430, and output device 440 are interconnected via a bus. Wherein:

[0207] The bus may include a path for transmitting information between various components of the computer system.

[0208] The processor 410 may be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0209] The processor 410 may include a main processor, and may also include a baseband chip, a modem, etc.

[0210] The memory 400 stores a program for executing the technical solution of the present invention, and may also store an operating system and other key business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory 400 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.

[0211] Input device 430 may include a device for receiving data and information input by a user, such as a keyboard, mouse, camera, scanner, light pen, voice input device, touch screen, pedometer, or gravity sensor.

[0212] Output device 440 may include a device that allows outputting information to a user, such as a display screen, printer, speaker, etc.

[0213] Communication interface 420 may include a device using any transceiver to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0214] Processor 410 executes programs stored in memory 400 and calls other devices, which can be used to implement the various steps of any of the wave creation methods provided in the above embodiments of this application.

[0215] Exemplary Computer Program Product and Storage Medium

[0216] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the wave creation methods according to various embodiments of this application described in any of the above embodiments of this specification.

[0217] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java, C++, etc., and also include conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0218] Furthermore, embodiments of this application may also be storage media storing a computer program thereon, the computer program being executed by a processor in the steps of the wave creation method according to various embodiments of this application described in any of the above embodiments of this specification, specifically implementing the following steps:

[0219] Obtaining cargo storage information of multiple pending-picking orders under the target storage area, the cargo storage information including the first lane information of the current lane, the current lane being the lane where the pending-picking goods are located in the pending-picking order;

[0220] Determining the lane score of each pending-picking order on each lane based on the first lane information, the lane score indicating the degree of concentration dependence of the picking path of the pending-picking order on each lane;

[0221] Determining the target lane with the highest order concentration based on the lane score;

[0222] Based on the lane score of the multiple pending-picking orders in the target lane, in the multiple pending-picking ordersAt least one target picking order is identified in the order and a wave is created, wherein the lane score corresponding to the at least one target picking order meets the preset screening conditions, wherein the preset screening conditions include at least one of the following: the lane score is greater than a preset score threshold, and the lane score is one of the top preset number of lanes with the highest lane score ranking.

[0223] For the foregoing method embodiments, for the sake of simplicity, they are all described as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0224] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments.

[0225] The steps in the methods of the various embodiments of this application can be adjusted, merged, and deleted in order according to actual needs, and the technical features recorded in each embodiment can be replaced or combined.

[0226] The modules and sub-modules in the devices and terminals in the various embodiments of this application can be merged, divided, and deleted according to actual needs.

[0227] In the several embodiments provided in this application, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the terminal embodiments described above are merely illustrative. For example, the division of modules or sub-modules is merely a logical functional division. In actual implementation, there may be other division methods. For example, multiple sub-modules or modules can be combined or integrated into another module, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical, or other forms.

[0228] The modules or sub-modules described as separate components may or may not be physically separate. The components that are modules or sub-modules may or may not be physical modules or sub-modules; that is, they may be located in one place or distributed across multiple network modules or sub-modules. Some or all of the modules or sub-modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0229] Furthermore, the functional modules or sub-modules in the various embodiments of this application may be integrated into one processing module, or each module or sub-module may exist physically separately, or two or more modules or sub-modules may be integrated.In a module. The above-mentioned integrated module or sub-module can be implemented in hardware or in the form of software functional modules or sub-modules. Specification 15 / 16 pages 19 CN 121235306 A

[0230] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of the various examples have been generally described in terms of functionality in the above description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0231] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly in hardware, software units executed by a processor, or a combination of both. The software unit may be housed in random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0232] Finally, it should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0233] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein. Specification 16 / 16 pages 20 CN 121235306 A Figure 1 Specification Drawings 1 / 4 pages 21 CN 121235306 A Figure 2 Specification Drawings 2 / 4Page 22 CN 121235306 A Figure 3 Description Drawings 3 / 4 Page 23 CN 121235306 A Figure 4 Description Drawings 4 / 4 Page 24 CN 121235306 A Abstract The present invention relates to a wave creation method, an electronic device and a storage medium, which are applied to the technical field of computers. The method comprises: acquiring goods storage information about a plurality of to-be-picked orders in a target storage site, where the goods storage information includes first aisle information of a current aisle, and the current aisle is an aisle where the to-be-picked goods in the to-be-picked orders are located; determining, based on the first aisle information, an aisle score for each to-be-picked order on each aisle; determining, based on the aisle scores, a target aisle having the highest order concentration; determining, based on the aisle scores of the plurality of to-be-picked orders, at least one target picking order among the plurality of to-be-picked orders in the target aisle, and creating a wave,where the at least one target picked-up order satisfies a preset screening condition based on the aisle score, and the preset screening condition includes at least one of: the aisle score being greater than a preset score threshold, or the aisle score being one of the top preset number of aisle scores having the highest ranking.

Claims

1. A method of creating a wave, characterized by, The method is applied to wave creation of picking orders of a target warehouse site, and the target warehouse site comprises a plurality of aisles, including: Obtaining goods storage information of a plurality of to-be-picked orders under a target warehouse site, the goods storage information comprising first aisle information of a current aisle, the current aisle being an aisle where goods to be picked in the to-be-picked orders are located; Determining aisle scores of each of the to-be-picked orders on each aisle based on the first aisle information, the aisle score indicating a degree of concentration of a picking path of the to-be-picked order on each aisle; Determining a target aisle with the highest order concentration degree based on the aisle scores; Determining at least one target picking order from the plurality of to-be-picked orders based on the aisle scores of the plurality of to-be-picked orders in the target aisle and creating a wave, wherein the aisle score corresponding to the at least one target picking order satisfies a preset screening condition, and the preset screening condition comprises at least one of the following: the aisle score is greater than a preset score threshold, and the aisle score is one of a top preset number of aisle scores with the highest rankings.

2. The method of claim 1, wherein, Determining the aisle scores of each of the to-be-picked orders on each aisle based on the first aisle information comprises: Obtaining a total score of all aisles in the target warehouse site; Determining a covered aisle in the aisles based on the first aisle information, the covered aisle being an aisle covered by a picking path when picking the to-be-picked orders; Determining a first aisle score of the covered aisle according to second aisle information of the covered aisle and the total score of the aisles; Determining a second aisle score of other aisles according to a positional relationship between the other aisles and the covered aisle and the first aisle score, the other aisles being aisles other than the covered aisle in the target warehouse site; Determining the first aisle score and the second aisle score as the aisle score.

3. The method of claim 2, wherein, The first aisle information comprises position information of the current aisle in the target warehouse site; Determining the covered aisle in the aisles based on the first aisle information comprises: In a case where the number of the current aisles is one, determining the current aisle as the covered aisle; In a case where the number of the current aisles is more than two, determining two boundary aisles farthest apart from each other in the current aisles according to the position information; Determining the boundary aisles and aisles between the boundary aisles as the covered aisles.

4. The method of claim 2, wherein, The second aisle information comprises an aisle score of each of the covered aisles, and the first aisle score of the covered aisle is determined according to the second aisle information of the covered aisle and the total score of the aisles, comprising: Calculating a first sum of the aisle scores of each of the covered aisles; Determining a difference between the total score of the aisles and the first sum as the first aisle score.

5. The method of claim 2, wherein, Determining the second aisle score of the other aisles according to the positional relationship between the other aisles and the covered aisle and the first aisle score comprises: According to the positional relationship, the second aisle score of the other aisles is configured to be sequentially decreased in order from near to far from the covered aisle, and the second aisle score is less than the first aisle score.

6. The method of claim 1, wherein, The target aisle with the highest order concentration is determined based on the aisle scores, including: Based on the aisle scores of each of the to-be-picked orders in each of the aisles, a total aisle score of each of the aisles is determined; The target aisle is determined from the aisles based on the total aisle scores.

7. The method of claim 6, wherein, The target aisle is determined from the aisles based on the total aisle scores, including: A first maximum value in the total aisle scores is determined; In the case where the first maximum value is one, the aisle corresponding to the first maximum value is determined as the target aisle; In the case where the first maximum value is more than two, a second sum value of the total aisle scores of a first adjacent aisle adjacent to a candidate aisle and the first maximum value is calculated, the candidate aisle being the aisle corresponding to the first maximum value; The target aisle is determined based on the second sum value.

8. The method of claim 7, wherein, The target aisle is determined based on the second sum value, including: A second maximum value in the second sum value is determined; In the case where the second maximum value is more than two, the number of the first adjacent aisles is increased, and the second maximum value is determined again; In the case where the second maximum value is one, the candidate aisle corresponding to the second maximum value is determined as the target aisle.

9. The method of claim 1, wherein, In the case where the preset screening condition includes that the aisle score is one of the top preset number of aisle score rankings, the at least one target picking order is determined from the multiple to-be-picked orders based on the aisle scores of the multiple to-be-picked orders in the target aisle, and a wave is created, including: The multiple to-be-picked orders are sorted based on the aisle scores of the to-be-picked orders in the target aisle; In the case where there are at least two same type to-be-picked orders, a lane distribution of a previous to-be-picked order is determined, the same type to-be-picked orders being to-be-picked orders with the same aisle score, and the previous to-be-picked order being the nearest to-be-picked order before the target to-be-picked order; Based on the lane distribution, an extension score of each of the same type to-be-picked orders is calculated; The same type to-be-picked orders with the same aisle score are sorted according to the extension scores, to obtain a sorting result of the multiple to-be-picked orders; The top preset number of to-be-picked orders in the sorting result are determined as the target picking orders and a wave is created.

10. The method of claim 9, wherein, The lane distribution of the previous to-be-picked order is determined, including: A third sum value of the aisle scores of a second adjacent aisle adjacent to one side of the target aisle is calculated; A fourth sum value of the aisle scores of a third adjacent aisle adjacent to the other side of the target aisle is calculated; A target sum value of the greater of the third sum value and the fourth sum value is determined; The lane distribution is determined as being on one side of the adjacent aisle corresponding to the target sum value.

11. The method of claim 9, wherein, Based on the lane distribution, the extension score of each of the same type to-be-picked orders is calculated, including: An extension aisle in an extension direction of the target aisle is determined based on the lane distribution; The sum value of the aisle scores of the extension aisle and the target aisle is determined as the extension score.

12. An electronic device, comprising: It includes a memory and a processor; The memory is connected with the processor and is used for storing programs; The processor is configured to implement the wave batch creation method according to any one of claims 1 to 11 by running a program in the memory.

13. A storage medium, characterized by The storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the wave batch creation method according to any one of claims 1 to 11.

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