Warehouse-out management method

Abstract

This application discloses an outbound management method, comprising: obtaining multiple outbound orders included in an outbound wave, the quantity of each outbound order's product type, and the number of picking operations for each outbound order; calculating the distribution concentration of the outbound wave and the size of each outbound order; and, provided that the distribution balance meets preset conditions, dividing at least a portion of the outbound orders in the outbound wave according to product type based on the size of each outbound order, and assigning a new delivery port to each newly added outbound order. This application quantifies the distribution balance of the size of each outbound order in an outbound wave through distribution concentration, and optimizes the processing of abnormally large outbound orders through segmentation, making the delivery process smoother and reducing the probability of congestion in transportation devices and high order waiting costs during outbound operations, thereby improving outbound efficiency.

Description

Technical Field

[0001] This application relates to the field of logistics technology, and in particular to an outbound management method, a computer-readable storage medium, and an electronic device. Background Technology

[0002] In the logistics industry, outbound delivery is a crucial step. Outbound delivery refers to the process of delivering the various types of goods included in the outbound order to the delivery port.

[0003] When the goods are shipped out, a transport device can be used to move the boxes included in the outbound order. Each outbound order is assigned a delivery port, and the transport device delivers the boxes included in the outbound order to the assigned delivery port for outbound processing.

[0004] Given the current complex warehouse layout and the pursuit of warehouse operation efficiency, how to achieve outbound operations in a reasonable and efficient manner has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides an outbound management method, a computer-readable storage medium, an electronic device, and a computer program product to achieve reasonable and efficient outbound operations.

[0006] According to a first aspect of this application, an outbound management method is disclosed, comprising:

[0007] The system acquires multiple outbound orders included in each outbound wave, as well as the quantity of each product type included in each outbound order and the number of picking operations for each outbound order. The number of picking operations is used to characterize the number of deliveries required for the transportation device to process the outbound order. Each outbound order is assigned a corresponding delivery port.

[0008] Based on the quantity of product types included in each outbound order and the number of picking operations, the distribution concentration of the outbound wave and the volume of each outbound order are calculated; the distribution concentration is used to characterize the distribution balance of the volume of each outbound order in the outbound wave.

[0009] When the distribution balance meets the preset conditions, at least a portion of the outbound orders in the outbound wave are divided according to the product type based on the volume of each outbound order, and a new delivery port is assigned to each newly added outbound order.

[0010] According to a second aspect of this application, an outbound management device is disclosed, comprising:

[0011] The communication module is used to acquire multiple outbound orders included in the outbound wave, as well as the quantity of each type of goods included in each outbound order and the picking number of each outbound order. The picking number is used to characterize the number of deliveries required for the transportation device to process the outbound order. Each outbound order is assigned a corresponding delivery port.

[0012] The processor is configured to: calculate the distribution concentration of the outbound wave and the volume of each outbound order based on the quantity of the product types included in each outbound order and the number of picking operations; the distribution concentration is used to characterize the distribution balance of the volume of each outbound order in the outbound wave; when the distribution balance meets a preset condition, divide at least a portion of the outbound orders in the outbound wave according to the product type based on the volume of each outbound order, and assign a new delivery port to each newly added outbound order.

[0013] According to a third aspect of this application, an electronic device is disclosed, comprising: a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the outbound management method as described in the first aspect.

[0014] According to a fourth aspect of this application, a computer-readable storage medium is disclosed, on which a program is stored, which, when executed by the processor, implements the steps of the outbound management method as described in the first aspect.

[0015] According to a fifth aspect of this application, a computer program product is disclosed, the computer program product comprising a computer program that, when executed by a processor, implements the steps of the outbound management method as described in the first aspect.

[0016] In this embodiment, the distribution concentration of the outbound wave is calculated by the quantity of product types included in each outbound order and the number of picking operations for each outbound order. This quantifies the evenness of the volume distribution of each outbound order in the outbound wave. Based on the distribution concentration, outbound orders with uneven distribution in the outbound wave are identified. Outbound orders with abnormally large volumes are optimized by segmentation, making the volume distribution of each outbound order in the outbound wave more even. New delivery slots are assigned to the new orders segmented from the outbound wave, making the delivery process smoother. This reduces the probability of traffic congestion and high order waiting costs during outbound operations, thereby improving outbound efficiency. Attached Figure Description

[0017] Figure 1 This is a schematic diagram illustrating the implementation environment of some embodiments of the outbound management method of this application;

[0018] Figure 2 This is a flowchart of an outbound management method according to some embodiments of this application;

[0019] Figure 3 This is a distribution curve of the "health-wealth" concentration in some embodiments of this application;

[0020] Figure 4 This is a flowchart of an outbound management method according to some embodiments of this application;

[0021] Figure 5 These are schematic diagrams of the outbound management device according to some embodiments of this application;

[0022] Figure 6 This is a block diagram of an electronic device according to some embodiments of this application. Detailed Implementation

[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of this application.

[0025] With the development of intelligent technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data, the demand for transforming and upgrading the traditional logistics industry using these technologies is becoming increasingly strong. Intelligent Logistics System (ILS) has become a research hotspot in the logistics field. Intelligent logistics utilizes AI, big data, and various information sensors, radio frequency identification (RFID) technologies, Global Positioning System (GPS) and other IoT devices and technologies. It is widely applied to basic activities such as material transportation, warehousing, distribution, packaging, loading and unloading, and information services, enabling intelligent analysis and decision-making, automated operation, and high-efficiency optimization management of the material management process. IoT technologies include sensing devices, RFID, laser infrared scanning, and infrared sensing identification. The IoT can effectively connect materials in logistics to the network, monitor materials in real time, and sense environmental data such as humidity and temperature in warehouses to ensure the safe storage environment of materials. Big data technology can be used to sense and collect all data in logistics, upload it to the data layer of an information platform, and perform filtering, mining, and analysis on the data. Ultimately, this provides precise data support for business processes (such as transportation, warehousing, storage, picking, packaging, sorting, outbound, inventory, and delivery). The application of artificial intelligence in logistics can be broadly divided into two directions: 1) Using AI-enabled intelligent equipment such as unmanned trucks, Automated Guided Vehicles (AGVs), Autonomous Mobile Robots (AMRs), forklifts, shuttles, stacker cranes, unmanned delivery vehicles, drones, service robots, robotic arms, and smart terminals to replace some manual labor; 2) Improving manual efficiency through software systems driven by computer vision, machine learning, operations research, and other technologies or algorithms, such as transportation equipment management systems, warehouse management systems, equipment scheduling systems, and order allocation systems. With the research and advancement of smart logistics, this technology has been applied in numerous fields, such as retail and e-commerce, electronics, tobacco, pharmaceuticals, industrial manufacturing, footwear and apparel, textiles, and food.

[0026] Please refer to Figure 1 This diagram illustrates the implementation environment of an outbound management method provided in an embodiment of this application. Figure 1 As shown, one outbound wave in this implementation environment can include multiple outbound orders, and the material box of each outbound order can be transported to the corresponding delivery port for outbound processing via a transportation device.

[0027] Specifically, each outbound order may include one or more product types. The volume of an outbound order is directly proportional to the number of product types included in the order and the number of picking operations. Product type is also called product category; for example, products of the same type or category can be understood as products corresponding to the same model. Furthermore, product type can also refer to a certain attribute of the product. For example, if the product is food, the product type could refer to the product's weight specifications or flavor type; if the product is stationery, the product attribute could refer to any attribute such as stationery size or specifications. In this embodiment, product type generally refers to a single attribute of the product, describing the product from one attribute dimension. The specific content referred to by the product type can be set according to actual needs, and this embodiment does not limit this. The number of picking operations for an outbound order represents the number of deliveries required when processing the outbound order through a transportation device. The transportation device can be a handling equipment operating in the warehouse, such as AGVs, AMRs, or other handling robots, or it can be a box-type cargo handling robot, forklift, or other handling equipment.

[0028] In related technologies, multiple outbound orders within a single outbound wave can be linked to individual delivery points in the implementation scenario to achieve outbound processing. However, this approach presents the following problems: 1. When the volume of a current outbound order is significantly larger than other outbound orders, blockages may occur in the conveyor system at the material feeding channel, impacting outbound efficiency. 2. When the volume distribution of outbound orders within an outbound wave is uneven, processing smaller outbound orders can lead to a sharp increase in waiting costs for other larger outbound orders.

[0029] To address the aforementioned issues, this application embodiment can quantify a distribution concentration parameter for each outbound wave based on the distribution curve of the "health-wealth" concentration. This distribution concentration can be used to measure the balanced distribution of outbound order volume within each outbound wave. The smaller the distribution concentration of an outbound wave, the more balanced the distribution of outbound order volume within that wave, resulting in a lower probability of outbound orders with abnormally large or small volumes appearing in the wave, thus reducing the likelihood of the aforementioned problems occurring.

[0030] Therefore, the embodiments of this application can measure the distribution balance of outbound order volume in outbound waves based on distribution concentration, and segment abnormal volume orders in outbound waves with uneven order volume distribution until the distribution of outbound order volume in outbound waves tends to be balanced. This can reduce the probability of the above problems occurring and improve outbound efficiency.

[0031] For example, Figure 1In this embodiment, assuming order A is an exceptionally large outbound order in a wave of outbound shipments, according to relevant technologies, order A can be bound to delivery port a for outbound shipment. To solve the delivery congestion and waiting problems caused by order A, this application embodiment can split order A into order A-1 and order A-2, and continue to bind order A-1 to delivery port a, while binding the newly split order A-2 to another delivery port d. That is, the number of delivery ports is increased for the original order A, which can reduce the impact of order imbalance on outbound efficiency and improve the overall outbound efficiency of the wave.

[0032] Please refer to Figure 2 The diagram illustrates a flowchart of an outbound management method provided in an embodiment of this application. This outbound management method can be applied to... Figure 1 The implementation environment is shown. Figure 2 As shown, the outbound management method includes steps 101-103.

[0033] Step 101: Obtain multiple outbound orders included in the outbound wave, as well as the quantity of each product type included in each outbound order and the picking number of each outbound order. The picking number is used to characterize the number of deliveries required for the transportation device to process the outbound order; each outbound order is assigned a corresponding delivery port.

[0034] In this embodiment, each outbound order may include one or more product types, and each product type may include different individual items. An individual item can be understood as the minimum attribute of a product, and each individual item has a corresponding required quantity. For example, a customer requires quick-drying T-shirts, specifically 10 red quick-drying T-shirts and 20 blue quick-drying T-shirts. The number of picking operations for an outbound order can be determined by the required quantity of individual items in the outbound order and the carrying capacity of the transportation device. One picking operation represents one delivery operation of the transportation device.

[0035] Step 102: Calculate the distribution concentration of the outbound wave and the volume of each outbound order based on the quantity of the product types included in each outbound order and the number of picking operations; the distribution concentration is used to characterize the distribution balance of the volume of each outbound order in the outbound wave.

[0036] In practical applications, there exists a distribution curve for the "health-wealth" concentration ratio. This curve measures the inequality in the distribution of health variables relative to wealth variables. Health inequality related to wealth income can be assessed by plotting the cumulative health proportions of individuals from the poorest to the richest. Generally, the wealthier an individual is, the healthier they are, and vice versa. In this scenario, a concentration ratio C can be quantified to reflect the distribution of health variables relative to wealth variables.

[0037]

[0038] Where h is the health variable and R is the wealth variable; h i For ranking health variables, h i The larger the h, the richer the person. i The value of h ranges from 1 / 2n to (1-1 / 2n), resulting in a total of n rankings; i For ranking health variables, h i The bigger, the healthier and richer, h i The value range is 1 / 2n to (1-1 / 2n), with a total of n rankings; when the distribution concentration C = (1-n) / n, it indicates that all health is concentrated on the poorest individuals; when the distribution concentration C = (n-1) / n, it indicates that all health is concentrated on the richest individuals.

[0039] Furthermore, refer to Figure 3 The diagram illustrates a distribution curve of "health-wealth" concentration. The concentration C can be represented by a Lorenz curve, where twice the area a / b enclosed by the curve and the diagonal is the concentration C value. When the curve approaches the diagonal, the concentration C approaches 0, indicating a more equitable distribution of health and wealth. When the curve deviates from the diagonal, the concentration C approaches 1, indicating a more unequal distribution. A larger absolute value of the concentration C indicates a more unequal distribution of health and wealth variables. For example, if the area enclosed by the curve deviating from the diagonal is A+a, it means all health is possessed by the wealthiest individuals, indicating the most unequal distribution, with a concentration of 1. If the area enclosed by the curve deviating from the diagonal is B+b, it means all health is possessed by the poorest individuals, indicating the most unequal distribution, with a concentration of -1. Ideally, individuals, regardless of wealth, should have a equitable opportunity to possess health.

[0040] Based on the above analysis, a similar need for equality in the "health-wealth" distribution exists in the outbound scenario. This embodiment of the application can treat outbound waves as a group, each outbound order as an individual within that group, the quantity of product types included in each outbound order as a wealth variable, and the number of picks for each outbound order as a health variable. Based on the above formula for calculating distribution concentration, the distribution concentration of the outbound wave can be calculated from the quantity of product types and the number of picks. A higher distribution concentration indicates a more uneven distribution of the outbound orders within the outbound wave, resulting in lower outbound efficiency. Conversely, a lower distribution concentration indicates a more balanced distribution of the outbound orders within the outbound wave, resulting in higher outbound efficiency. Ideally, it is desirable that outbound orders, regardless of the quantity of product types they contain, have an equal distribution of picks, achieving a balanced distribution of the outbound orders within an outbound wave, thus preventing an excessive number of large-volume orders within each outbound wave.

[0041] In the actual order picking process, orders are generated continuously according to the same product type (the product types contained in an order are as similar as possible). This results in an uneven distribution of the volume of outbound orders in a single outbound wave (such as including orders with abnormally large volumes), which affects outbound efficiency. The embodiments of this application can use the distribution concentration to measure the distribution balance of the volume of each outbound order in a single outbound wave, and correspondingly carry out processing of outbound orders in outbound waves with uneven distribution, so that the volume distribution of each outbound order in the outbound wave tends to be balanced.

[0042] Step 103: When the distribution balance meets the preset conditions, at least a portion of the outbound orders in the outbound wave are divided according to the product type based on the volume of each outbound order, and a new delivery port is assigned to each newly added outbound order.

[0043] In this embodiment, since the distribution concentration is used to quantify the distribution balance of outbound orders in outbound waves, outbound waves with uneven distribution can be determined by the distribution concentration. At least some outbound orders in the uneven outbound waves can be optimized by segmentation. The aim is to divide each large outbound order in the outbound wave into multiple smaller outbound orders, so that the distribution of the size of each outbound order in the outbound wave is balanced. A new delivery port is assigned to each newly segmented outbound order, thereby reducing the probability of transportation device congestion and high order waiting costs during outbound operations and improving outbound efficiency.

[0044] Specifically, orders can be segmented based on product type, such as... Figure 1Orders A that are unusually large can be split into orders A-1 and A-2. Order A-1 is then bound to delivery port a, and order A-2 is bound to delivery port d. This increases the number of delivery ports for the original order A, which can reduce the impact of order imbalance on outbound efficiency and improve the overall outbound efficiency of each wave.

[0045] In summary, the outbound management method provided in this application quantifies the distribution balance of the outbound wave by calculating the distribution concentration of the outbound wave based on the quantity of goods included in each outbound order and the number of picking operations for each outbound order. It then identifies outbound orders with uneven distribution within the outbound wave based on the distribution concentration and optimizes the processing of abnormally large outbound orders by segmentation. This ensures a balanced distribution of the outbound order volume within the outbound wave. Furthermore, it assigns new delivery points to the newly segmented orders from the outbound wave, facilitating smoother delivery and reducing the likelihood of congestion in transportation devices and high order waiting costs during outbound operations, thereby improving outbound efficiency.

[0046] This application provides another outbound management method. (Refer to...) Figure 4 The outbound management method includes steps 201-205.

[0047] Step 201: Obtain multiple outbound orders included in the outbound wave, as well as the quantity of each product type included in each outbound order and the picking number of each outbound order. The picking number is used to characterize the number of deliveries required for the transportation device to process the outbound order; each outbound order is assigned a corresponding delivery port.

[0048] For details of this step, please refer to step 101 above, which will not be repeated here.

[0049] Step 202: The product of the quantity of the product types included in each outbound order and the number of picking is used as the volume of each outbound order.

[0050] In this embodiment, the quantity of product types included in each outbound order and the number of picking operations for each outbound order typically reflect the time cost of the outbound order. The more product types included in an outbound order, the longer the outbound time; similarly, the more picking operations an outbound order involves, the longer the outbound time. This embodiment can also reflect this time cost through the size of the outbound order; a larger outbound order indicates a large order, and thus a higher time cost. Furthermore, based on the relationship between the quantity of product types, the number of picking operations, and the outbound time cost, the product of the quantity of product types and the number of picking operations can be used as the size of the outbound order.

[0051] Step 203: Calculate the distribution concentration of the outbound waves based on the quantity of product types included in each outbound order and the number of picking operations for each outbound order.

[0052] For details of this step, please refer to step 102 above, which will not be repeated here.

[0053] Optionally, step 203 may specifically include:

[0054] Sub-step 2031: Calculate the average number of picking operations for all outbound orders under the outbound wave based on the number of picking operations for each outbound order.

[0055] Sub-step 2032: Sort all outbound orders included in the warehouse wave according to the quantity of the product type to obtain a first sorting result.

[0056] Sub-step 2033: Calculate the distribution concentration of the outbound wave based on the number of outbound orders included in the outbound wave, the first sorting result, the average picking count, and the picking count of the outbound order. The distribution concentration is inversely proportional to the distribution balance of the volume of each outbound order in the outbound wave.

[0057] In this embodiment of the application, for sub-steps 2031-2033, the outbound waves can be regarded as a group P based on the calculation formula of the distribution concentration C in step 102 above. i Each outbound order is considered as an individual p in a group. ij The quantity of each type of goods included in each outbound order. Replace the wealth variable in the original formula with the number of picks for each outbound order. Replace the health variable in the original formula, and calculate the distribution concentration c of the reservoir waves using the following formula. i :

[0058] Where 1≤i≤M, M is the number of outbound waves; 1≤j≤N i N i The quantity of outbound orders under each outbound wave; m i This represents the average number of picks for all outbound orders in the outbound wave. r ij The first sorting result is obtained by sorting all outbound orders in the outbound wave according to the quantity of product type. In one implementation, the outbound orders in the outbound wave can be sorted first in ascending order of the quantity of product type. For outbound orders with the same quantity of product type, they can be further sorted in ascending order of the number of picking to obtain the first sorting result.

[0059] In this embodiment, the distribution concentration C' can be used to measure the distribution balance of outbound orders in an outbound wave. The larger the distribution concentration C', the more uneven the distribution of outbound orders in the outbound wave, resulting in poor outbound efficiency. Conversely, the smaller the distribution concentration C', the more balanced the distribution of outbound orders in the outbound wave, resulting in higher outbound efficiency. Subsequently, processing can be carried out on outbound orders in outbound waves with uneven distribution to make the distribution of outbound orders in the outbound wave more balanced, thereby improving outbound efficiency.

[0060] Step 204: Pre-segment at least a portion of the outbound orders in the outbound waves according to the product type, and calculate the distribution concentration update value of the outbound waves based on the pre-segmented outbound waves.

[0061] In this embodiment, a pre-segmentation operation can be performed on each outbound wave. Based on the pre-segmented outbound waves, the updated distribution concentration value of the outbound waves after pre-segmentation is calculated. The difference between the distribution concentration calculated before pre-segmentation and the updated distribution concentration value after pre-segmentation is used to determine whether the outbound orders under that outbound wave require further optimization. When the difference is positive, it indicates that the distribution concentration decreases after pre-segmentation, and the order volume distribution of that outbound wave becomes more balanced, thus producing an optimization effect. When the difference is negative, it indicates that the distribution concentration increases after pre-segmentation, and the order volume distribution of that outbound wave becomes more unbalanced, resulting in a negative effect. To achieve a better optimization effect, this embodiment can set a threshold value greater than or equal to a first threshold to determine that the order volume distribution of that outbound wave is unbalanced and has a high optimization requirement, after which the actual segmentation of that outbound wave can be performed.

[0062] It's important to note that pre-segmentation refers to a hypothetical segmentation operation performed on outbound orders within a shipment wave based on product type. No actual segmentation is performed; its purpose is primarily to evaluate the effectiveness of subsequent actual segmentation operations based on the pre-segmentation results. The segmentation logic of pre-segmentation and actual segmentation is consistent: both aim to divide large outbound orders in a shipment wave into multiple smaller orders through simulated segmentation, resulting in a more balanced distribution of order volume across the shipment wave. In practical applications, pre-segmentation does not assign unique codes to the resulting sub-orders, while the actual segmentation operation assigns a unique code to each sub-order after completion.

[0063] Optionally, the volume of the outbound order is directly proportional to the number of product types included in the outbound order and the number of picking operations in the outbound order; step 204 may specifically include:

[0064] Sub-step 2041: Determine the first outbound order with the largest current volume in the outbound wave.

[0065] Sub-step 2042: Pre-segment the first outbound order according to the product type to obtain the pre-segmented new outbound orders.

[0066] In the embodiments of this application, whether it is pre-segmentation or segmentation operation, the purpose is to divide the large outbound orders in the outbound wave into multiple smaller outbound orders, so that the order volume distribution of the outbound wave is balanced. Therefore, when performing pre-segmentation, the first outbound order with the largest current volume in the outbound wave can be determined in real time, and the first outbound order can be pre-segmented according to the product type, thereby dividing the first outbound order into multiple sub-orders. Then, the orders in the outbound wave are updated, and the first outbound order with the largest volume in the updated outbound wave is found again to continue segmentation until the order volume distribution in the outbound wave is balanced, at which point the pre-segmentation stops and the pre-segmentation result is obtained.

[0067] Specifically, during pre-segmentation, the order needs to be segmented according to the number of segmentation steps s, where s = num + 1, and num is the number of sub-orders that were previously segmented from the first outbound order in the outbound wave (sub-orders obtained by segmentation methods other than the pre-segmentation in step 204 and the segmentation operation in step 205 of this application embodiment). Specifically, during segmentation, the order can be sorted in reverse order according to the number of picking times of the product types of the original first outbound order (the first outbound order that has never been segmented). Then, the product types in the sorting results are allocated to s different sets one by one. During the allocation process, it is ensured that the difference between the total number of picking times of the largest set and the total number of picking times of the smallest set is less than or equal to a preset difference threshold, thereby achieving balanced allocation.

[0068] Step 205: When the difference between the distribution concentration degree and the updated distribution concentration degree value is greater than or equal to the first threshold, at least a portion of the outbound orders in the outbound wave are divided according to the product type based on the volume of each outbound order to obtain the new outbound order.

[0069] In this embodiment, based on the difference between the distribution concentration calculated before pre-segmentation and the updated distribution concentration after pre-segmentation for each outbound wave, it can be determined whether the outbound orders under that outbound wave need further optimization. In order to achieve better optimization results, this embodiment can set that when the difference is greater than or equal to a first threshold, it is determined that the order volume distribution of that outbound wave is unbalanced and has a high optimization demand, and then the actual segmentation of that outbound wave can be carried out.

[0070] After performing a true segmentation operation on the outbound waves, the larger outbound orders in the outbound waves are divided into multiple smaller outbound orders, which makes the order size distribution in the outbound waves more balanced. New delivery ports are also assigned to the new orders segmented from the outbound waves, making the delivery process smoother. This reduces the probability of traffic congestion and high order waiting costs during outbound operations, thereby improving outbound efficiency.

[0071] Optionally, in one implementation, the volume of the outbound order is directly proportional to the number of product types included in the outbound order and the number of picking operations in the outbound order; step 205 may specifically include:

[0072] Sub-step 2051: Continuously divide the second outbound order with the largest current volume in the outbound wave according to the product type, and update the volume of each outbound order in the outbound wave based on the newly added outbound orders obtained from the division.

[0073] Sub-step 2052: Calculate the updated distribution concentration value of the outbound waves based on the updated outbound waves.

[0074] Sub-step 2053: If the difference between the distribution concentration degree and the updated distribution concentration degree value is less than or equal to the second threshold, or if the number of newly added outbound orders in the segmentation result is equal to the upper limit of the newly added delivery port, the segmentation is stopped.

[0075] In this embodiment of the application, for sub-steps 2051-2053, the purpose of the segmentation operation is to divide the larger outbound orders in the outbound wave into multiple smaller outbound orders, so that the order volume distribution of the outbound wave is balanced. Specifically, during the segmentation, the second largest outbound order in the current outbound wave can be determined in real time, and the second outbound order can be segmented according to the product type, thereby dividing the second outbound order into multiple sub-orders. Then, the orders in the outbound wave are updated, and the second largest outbound order in the updated outbound wave is found again to continue segmentation until the order volume distribution in the outbound wave is balanced, at which point the segmentation stops and the segmentation result is obtained.

[0076] Specifically, after each segmentation, the distribution concentration update value of an outbound wave can be calculated, and the difference between the distribution concentration before and after the segmentation is calculated. If the difference between the distribution concentration and the updated distribution concentration value is less than or equal to a second threshold, the distribution of order volume in the current outbound wave is considered to be relatively balanced, and the segmentation can be stopped. Alternatively, if the number of newly added outbound orders in the segmentation result equals the upper limit of the new delivery slots, it can be considered that there are no new delivery slots available to allocate to the newly added orders in the current implementation environment, and the segmentation is stopped.

[0077] Optionally, the upper limit for the new delivery slot is obtained through the following steps:

[0078] Sub-step A1: Obtain the number of outbound waves included in the current batch, the total number of outbound orders, and the preset delivery port increase ratio.

[0079] Sub-step A2: Obtain the upper limit of the newly added delivery port based on the product of the number of outbound waves, the increase ratio of the delivery port, and the total number of outbound orders in the current batch.

[0080] In this embodiment of the application, a delivery port increase ratio can be set first based on the usage of delivery ports in the implementation environment. This ratio limits the proportion of delivery ports that can be allocated to new orders under the current delivery port load.

[0081] Furthermore, the product of the number of outbound waves included in the current batch, the increase ratio of delivery ports, and the total number of outbound orders in the current batch can be used as the upper limit for the number of new delivery ports.

[0082] For example, assuming the current batch includes 3 outbound waves, and each outbound wave includes 5 outbound orders, then the current batch has a demand for 15 delivery ports. If the delivery port increase ratio r = 20%, then the upper limit of the new delivery ports = 3 × 5 × 20% = 3.

[0083] Optionally, in another implementation, step 205 may specifically include:

[0084] Sub-step 2054: Obtain the historical number of splits for each of the outbound orders.

[0085] Sub-step 2055: Obtain the number of picks for each product type included in each outbound order.

[0086] Sub-step 2056: Sort all product types included in the outbound order according to the number of picking times for each product type to obtain a second sorting result.

[0087] Sub-step 2057: Starting from one end of the second sorting result, the product types are sequentially divided into n sets to complete the segmentation. The difference in the number of picking times between different sets is less than or equal to a third threshold, where n is determined by the historical segmentation times of each outbound order in the outbound wave.

[0088] Specifically, in one implementation, for sub-steps 2054-2056, the segmentation needs to be performed according to the segmentation number s', where s' = num' + 1, and num' is the number of sub-orders that have been segmented from the largest outbound order in the outbound wave, i.e., the historical segmentation number of the outbound order. Specifically, during the segmentation, the original outbound orders (the largest outbound orders that have never been segmented) can first be sorted in descending order by the number of pickings of the product types. Then, the product types in the second sorting result are assigned to s' different sets one by one. During the allocation process, it is ensured that the difference between the total number of pickings of the largest set and the total number of pickings of the smallest set is less than or equal to the third threshold, thereby achieving a balanced allocation.

[0089] In summary, the outbound management method provided in this application quantifies the distribution balance of the outbound wave by calculating the distribution concentration of the outbound wave based on the quantity of goods included in each outbound order and the number of picking operations for each outbound order. It then identifies outbound orders with uneven distribution within the outbound wave based on the distribution concentration and optimizes the processing of abnormally large outbound orders by segmentation. This ensures a balanced distribution of the outbound order volume within the outbound wave. Furthermore, it assigns new delivery points to the newly segmented orders from the outbound wave, facilitating smoother delivery and reducing the likelihood of congestion in transportation devices and high order waiting costs during outbound operations, thereby improving outbound efficiency.

[0090] Figure 5 These are schematic diagrams illustrating the structure of an outbound management device according to some embodiments of this application. For example... Figure 5 As shown, the outbound management device may include a communication module 301 and a processor 302.

[0091] The communication module 301 is used to acquire multiple outbound orders included in the outbound wave, as well as the quantity of the product types included in each outbound order and the picking number of each outbound order. The picking number is used to characterize the number of deliveries required by the transportation device to process the outbound order. Each outbound order is assigned a corresponding delivery port.

[0092] The processor 302 is configured to: calculate the distribution concentration of the outbound wave and the volume of each outbound order based on the quantity of the product types included in each outbound order and the number of picking operations; the distribution concentration is used to characterize the distribution balance of the volume of each outbound order in the outbound wave; when the distribution balance meets a preset condition, according to the volume of each outbound order, at least a portion of the outbound orders in the outbound wave are divided according to the product types, and a new delivery port is assigned to each newly added outbound order.

[0093] Optionally, the processor 302 is specifically used for:

[0094] At least a portion of the outbound orders in the outbound waves are pre-segmented according to the product type, and the distribution concentration update value of the outbound waves is calculated based on the pre-segmented outbound waves.

[0095] When the difference between the distribution concentration and the updated distribution concentration is greater than or equal to a first threshold, at least a portion of the outbound orders in the outbound wave are divided according to the product type based on the volume of each outbound order, to obtain the new outbound orders.

[0096] Optionally, the size of the outbound order is directly proportional to the number of product types included in the outbound order and the number of picking operations in the outbound order;

[0097] The processor 302 is specifically used for:

[0098] Identify the first outbound order with the largest current volume in the aforementioned outbound wave;

[0099] The first outbound order is pre-segmented according to the product type to obtain the pre-segmented new outbound orders.

[0100] Optionally, the volume of the outbound order is directly proportional to the number of product types included in the outbound order and the number of picking operations in the outbound order; the processor 302 is specifically used for:

[0101] The second largest outbound order in the outbound wave is continuously segmented according to the product type, and the volume of each outbound order in the outbound wave is updated based on the newly added outbound orders generated from the segmentation.

[0102] Based on the updated outbound wave number, calculate the updated distribution concentration value of the outbound wave number;

[0103] The segmentation stops when the difference between the distribution concentration and the updated distribution concentration is less than or equal to the second threshold, or when the number of newly added outbound orders is equal to the upper limit of the new delivery port.

[0104] Optionally, the processor 302 is specifically used for:

[0105] Get the number of outbound waves included in the current batch, the total number of outbound orders, and the preset delivery point increase ratio;

[0106] The upper limit of the newly added delivery ports is obtained by multiplying the number of outbound waves, the increase ratio of the delivery ports, and the total number of outbound orders in the current batch.

[0107] Optionally, the processor 302 is specifically used for:

[0108] The product of the quantity of the product types included in each outbound order and the number of picking operations is used as the volume of each outbound order.

[0109] Optionally, the processor 302 is specifically used for:

[0110] Calculate the average number of picks for all outbound orders in the outbound wave based on the number of picks for each outbound order;

[0111] Based on the quantity of the product type, all outbound orders included in the warehouse wave are sorted to obtain a first sorting result;

[0112] Based on the number of outbound orders included in the outbound wave, the first sorting result, the average number of picking operations, and the number of picking operations for each outbound order, the distribution concentration of the outbound wave is calculated. The distribution concentration is inversely proportional to the distribution balance of the volume of each outbound order in the outbound wave.

[0113] Optionally, the communication module 301 is further configured to:

[0114] Obtain the historical segmentation count for each outbound order; and obtain the picking count for each product type included in each outbound order;

[0115] The processor 302 is specifically used for:

[0116] Based on the number of times each product type is picked, all product types included in the outbound order are sorted to obtain a second sorting result;

[0117] Starting from one end of the second sorting result, the product types are sequentially divided into n sets to complete the segmentation. The difference in the number of picking times between different sets is less than or equal to a third threshold, where n is determined by the historical segmentation times of each outbound order in the outbound wave.

[0118] In summary, the outbound management device provided in this application quantifies the distribution balance of the outbound wave by calculating the distribution concentration of the outbound wave based on the quantity of product types included in each outbound order and the number of picking operations for each outbound order. It then identifies outbound orders with uneven distribution within the outbound wave based on the distribution concentration and optimizes the processing of abnormally large outbound orders by segmentation. This ensures a balanced distribution of the outbound order volume within the outbound wave and assigns new delivery slots to the newly segmented orders from the outbound wave, making the delivery process smoother. This reduces the likelihood of congestion in transportation devices and high order waiting costs during outbound operations, thereby improving outbound efficiency.

[0119] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0120] In addition, this application also provides an electronic device, which can be referred to in detail. Figure 6 The device 700 includes a processor 710, a memory 720, and a computer program stored in the memory 720 and executable on the processor 710. When the computer program is executed by the processor 710, it implements the various processes of the outbound management method embodiment described above and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0121] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements the various processes of the above-described outbound management method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0122] This application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described outbound management method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0123] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0124] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0126] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0127] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0128] 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, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device 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 terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0129] The above provides a detailed description of the outbound management method, apparatus, electronic device, and computer storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An outbound management method, characterized in that, include: The system acquires multiple outbound orders included in each outbound wave, as well as the quantity of each product type included in each outbound order and the number of picking operations for each outbound order. The number of picking operations is used to characterize the number of deliveries required for the transportation device to process the outbound order. Each outbound order is assigned a corresponding delivery port. Based on the quantity of product types included in each outbound order and the number of picking operations, the distribution concentration of the outbound wave and the volume of each outbound order are calculated; the distribution concentration is used to characterize the distribution balance of the volume of each outbound order in the outbound wave. When the distribution balance meets the preset conditions, at least a portion of the outbound orders in the outbound wave are divided according to the product type based on the volume of each outbound order, and a new delivery port is assigned to each newly added outbound order. The step of calculating the distribution concentration of the outbound waves based on the quantity of product types included in each outbound order and the number of picking operations includes: Calculate the average number of picks for all outbound orders in the outbound wave based on the number of picks for each outbound order; Based on the quantity of the product type, all outbound orders included in the warehouse wave are sorted to obtain a first sorting result; Based on the number of outbound orders included in the outbound wave, the first sorting result, the average number of picking operations, and the number of picking operations for each outbound order, the distribution concentration of the outbound wave is calculated. The distribution concentration is inversely proportional to the distribution balance of the volume of each outbound order in the outbound wave.

2. The method according to claim 1, characterized in that, When the distribution balance meets the preset conditions, the process involves dividing at least a portion of the outbound orders in each outbound wave according to the product type, based on the volume of each outbound order, including: At least a portion of the outbound orders in the outbound waves are pre-segmented according to the product type, and the distribution concentration update value of the outbound waves is calculated based on the pre-segmented outbound waves. When the difference between the distribution concentration and the updated distribution concentration is greater than or equal to a first threshold, at least a portion of the outbound orders in the outbound wave are divided according to the product type based on the volume of each outbound order to obtain the new outbound order.

3. The method according to claim 2, characterized in that, The volume of the outbound order is directly proportional to the number of product types included in the outbound order and the number of picking operations in the outbound order. At least a portion of the outbound orders in the aforementioned outbound waves are pre-segmented according to the aforementioned product type, including: Identify the first outbound order with the largest current volume in the aforementioned outbound wave; The first outbound order is pre-segmented according to the product type to obtain the pre-segmented new outbound orders.

4. The method according to claim 1, characterized in that, The volume of the outbound order is directly proportional to the number of product types included in the outbound order and the number of picking operations in the outbound order. The step of dividing at least a portion of the outbound orders in the outbound wave according to the product type based on the volume of each outbound order includes: The second largest outbound order in the outbound wave is continuously segmented according to the product type, and the volume of each outbound order in the outbound wave is updated based on the newly added outbound orders generated from the segmentation. Based on the updated outbound wave number, calculate the updated distribution concentration value of the outbound wave number; The segmentation stops when the difference between the distribution concentration and the updated distribution concentration is less than or equal to the second threshold, or when the number of newly added outbound orders is equal to the upper limit of the new delivery port.

5. The method according to claim 4, characterized in that, The upper limit value of the newly added delivery slot is obtained through the following steps: Get the number of outbound waves included in the current batch, the total number of outbound orders, and the preset delivery point increase ratio; The upper limit of the newly added delivery ports is obtained by multiplying the number of outbound waves, the increase ratio of the delivery ports, and the total number of outbound orders in the current batch.

6. The method according to any one of claims 1-5, characterized in that, The step of calculating the volume of each outbound order based on the quantity of the product types included in each outbound order and the number of picking operations includes: The product of the quantity of the product types included in each outbound order and the number of picking operations is used as the volume of each outbound order.

7. The method according to claim 6, characterized in that, The method further includes: Obtain the historical number of splits for each of the aforementioned outbound orders; The step of dividing at least a portion of the outbound orders in the outbound wave according to the product type based on the volume of each outbound order includes: Obtain the number of picks for each product type included in each of the outbound orders; Based on the number of picking operations for each product type, all product types included in the outbound order are sorted to obtain a second sorting result; Starting from one end of the second sorting result, the product types are sequentially divided into n sets to complete the segmentation. The difference in the number of picking times between different sets is less than or equal to a third threshold, where n is determined by the historical segmentation times of each outbound order in the outbound wave.

8. The method according to any one of claims 1-5, characterized in that, The method further includes: Obtain the historical number of splits for each of the aforementioned outbound orders; The step of dividing at least a portion of the outbound orders in the outbound wave according to the product type based on the volume of each outbound order includes: Obtain the number of picks for each product type included in each of the outbound orders; Based on the number of picking operations for each product type, all product types included in the outbound order are sorted to obtain a second sorting result; Starting from one end of the second sorting result, the product types are sequentially divided into n sets to complete the segmentation. The difference in the number of picking times between different sets is less than or equal to a third threshold, where n is determined by the historical segmentation times of each outbound order in the outbound wave.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the steps of the outbound management method as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the outbound management method as described in any one of claims 1 to 8.

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