Stocking warehouse joint control management method and platform for cross-border e-commerce

Abstract

The present invention relates to a method and platform for joint control management of stocking warehouses for cross-border e-commerce, and relates to the field of intelligent warehouse management, including: obtaining multiple floating cross-border transfer times according to historical cargo scheduling record analysis; optimizing the warehouse joint control scheme according to multiple floating cross-border transfer times, multiple distributed cargo quantities and multiple stocking frequencies, and obtaining the optimal warehouse joint control scheme, wherein the optimization is performed to reduce the cross-border transfer time, improve the balance of the transfer, and reduce the total probability of the cross-border transfer time between multiple warehouses after the transfer; and the optimal warehouse joint control scheme is used for transfer management. The present invention can solve the problems that the traditional inventory scheduling management method fails to effectively integrate and analyze the global inventory data, and there are problems such as low scheduling efficiency, unbalanced inventory resources and unstable transfer time; the above method can not only effectively reduce the cross-border transfer time, but also improve the balance of inventory, reduce inventory backlogs and reduce supply chain fluctuations.

Description

Technical Field

[0001] The present invention relates to the field of intelligent warehouse management, and in particular to a method and platform for joint control management of stocking warehouses for cross-border e-commerce. Background Art

[0002] Cross-border e-commerce refers to the trading of goods and services across borders through the Internet. With the advancement of globalization and the development of Internet technology, cross-border e-commerce has become an important part of global trade, changing traditional trade methods and enabling companies to break through national borders, sell products directly to all parts of the world, and purchase goods from other countries and regions.

[0003] With the continuous development of cross-border e-commerce business, traditional inventory scheduling management methods can no longer adapt to the increasingly complex global supply chain and multi-warehouse business environment. At present, the existing traditional inventory scheduling management methods usually rely on the local data of each warehouse, lack of global inventory data integration and analysis, and have problems such as low scheduling efficiency, unbalanced inventory resources, and unstable transfer time. Summary of the invention

[0004] The present invention aims to solve the problems that traditional inventory scheduling management methods used in cross-border e-commerce fail to effectively integrate and analyze global inventory data, and have low scheduling efficiency, unbalanced inventory resources, and unstable transfer timeliness. A method and platform for joint control of inventory storage for cross-border e-commerce is provided to solve the problems.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] In a first aspect, the present invention provides a method for managing cross-border e-commerce stocking warehouse joint control, comprising: in response to a current stocking demand, when the quantity of goods in a matching warehouse corresponding to the stocking demand does not meet the storage constraint, obtaining multiple distributed quantities of goods in other multiple supporting warehouses, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations; according to the historical cargo scheduling records of the matching warehouse and the multiple supporting warehouses, analyzing and obtaining multiple average cross-border transfer times and multiple cross-border transfer time floating parameters, and compensating to obtain multiple floating cross-border transfer times; according to the multiple floating cross-border transfer times and multiple distributed quantities of goods, and collecting the stocking frequencies of multiple warehouses, optimizing the warehouse joint control scheme to obtain the optimal warehouse joint control scheme, wherein the optimization is performed by reducing the cross-border transfer time, improving the balance of the quantity of goods in multiple warehouses after the transfer, and reducing the total probability of cross-border transfer time between multiple warehouses after the transfer, and the optimal warehouse joint control scheme includes the optimal transfer support warehouse; using the optimal warehouse joint control scheme, transfer management is performed from the optimal transfer support warehouse to the matching warehouse according to the stocking demand.

[0007] In a second aspect, the present invention provides a stocking warehouse joint control management platform for cross-border e-commerce, including: a stocking demand analysis module, which is used to respond to the current stocking demand, and when the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the storage constraint, obtain multiple distributed quantities of goods in other multiple supporting warehouses, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations; a floating cross-border transfer time acquisition module, which is used to analyze and obtain multiple average cross-border transfer times and multiple cross-border transfer time floating parameters based on the historical cargo scheduling records of the matching warehouse and the multiple supporting warehouses, and compensate for multiple floating Cross-border transfer time; a warehouse joint control scheme optimization module, which is used to optimize the warehouse joint control scheme according to the multiple floating cross-border transfer times and multiple distributed cargo quantities, and collect the stocking frequency of multiple warehouses to obtain the optimal warehouse joint control scheme, wherein the cross-border transfer time is optimized to reduce the cross-border transfer time, improve the balance of cargo quantities in multiple warehouses after the transfer, and reduce the total probability of cross-border transfer time between multiple warehouses after the transfer. The optimal warehouse joint control scheme includes an optimal transfer support warehouse; a transfer management module is used to adopt the optimal warehouse joint control scheme to manage the transfer of goods from the optimal transfer support warehouse to the matching warehouse according to the stocking demand.

[0008] In a third aspect, the present invention further provides an electronic device, comprising:

[0009] At least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor so that the at least one processor can perform the steps of any one of the methods described in the first aspect above.

[0010] In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed, the steps of the method described in any one of the first aspects are implemented.

[0011] The beneficial effects of the present invention are as follows: by responding to the current stocking demand, when the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the warehousing constraints, multiple distributed quantities of goods in other multiple supporting warehouses are obtained, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations; then, based on the historical cargo scheduling records of the matching warehouse and the multiple supporting warehouses, multiple average cross-border transfer times and multiple cross-border transfer time floating parameters are analyzed and obtained, and multiple floating cross-border transfer times are compensated; then, based on the multiple floating cross-border transfer times and multiple distributed quantities of goods, and the stocking frequencies of multiple warehouses are collected, the warehousing joint control plan is optimized to obtain the optimal warehousing joint control plan A solution is proposed, wherein the cross-border transfer time is optimized by reducing the cross-border transfer time, improving the balance of the quantity of goods in multiple warehouses after the transfer, and reducing the total probability of cross-border transfer time between multiple warehouses after the transfer, and the optimal warehouse joint control solution includes an optimal transfer support warehouse; finally, the optimal warehouse joint control solution is adopted to manage the transfer of goods from the optimal transfer support warehouse to the matching warehouse according to the stocking demand; the above method can improve the flexibility, comprehensiveness and accuracy of the cargo scheduling strategy setting, which can not only effectively reduce the cross-border transfer time, but also improve inventory balance, reduce inventory backlogs and reduce supply chain fluctuations, realize efficient and accurate cross-border cargo scheduling, and significantly improve resource utilization and overall operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A schematic diagram of the process of the method for joint control of stocking warehouses for cross-border e-commerce provided by the present invention;

[0013] Figure 2 A schematic diagram of the structure of a stocking warehouse joint control management platform for cross-border e-commerce provided by the present invention;

[0014] Figure 3 A schematic diagram of the structure of an electronic device provided by the present invention;

[0015] Figure 4 A schematic diagram of the structure of a computer-readable storage medium provided by the present invention.

[0016] In the accompanying drawings, the components represented by the reference numerals are described as follows:

[0017] Stocking demand analysis module 01, floating cross-border transfer time acquisition module 02, warehouse joint control plan optimization module 03, transfer management module 04, electronic device 500, memory 510, processor 520, first computer program 511, computer readable storage medium 600, second computer program 611. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0019] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0020] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0021] Embodiment 1, as Figure 1 As shown, the embodiment of the present invention provides a method for joint control management of stocking warehouse for cross-border e-commerce, which specifically includes the following steps:

[0022] S100: In response to the current stocking demand, when the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the storage constraint, obtain multiple distributed quantities of goods in other multiple supporting warehouses, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations.

[0023] Furthermore, step S100 of the present invention further includes:

[0024] S110: In response to the current stocking demand, obtain the stocking quantity and stocking address within the stocking demand; S120: According to the stocking address, match the nearest warehouse among multiple warehouses as a matching warehouse, and obtain the quantity of goods in the matching warehouse, wherein the multiple warehouses are distributed in multiple locations; S130: Subtract the stocking quantity from the quantity of goods to obtain the remaining quantity of goods, and determine whether the remaining quantity of goods is greater than or equal to the emergency quantity threshold of the matching warehouse. If so, the storage constraint is met, and if not, the storage constraint is not met; S140: When the storage constraint is not met, obtain the quantity of goods in other multiple warehouses, and obtain multiple support warehouses that meet the storage constraint based on the stocking quantity calculation and judgment, and obtain the quantity of goods in the multiple support warehouses as multiple distributed quantity of goods.

[0025] Specifically, the order management system accepts the current stocking demand, obtains the stocking quantity and stocking address in the stocking demand, wherein the stocking quantity includes the stocking commodity type and the demand quantity (such as 100 down jackets), and the stocking address refers to the target warehouse or the delivery location specified by the customer, which can be a warehouse in a specified country or region, or a delivery address directly pointing to the customer. Then, according to the stocking address, the warehouse closest to the multiple warehouses (with the shortest transportation distance) is matched as the matching warehouse, wherein the multiple warehouses are distributed in multiple cross-border locations, and the quantity of goods of the same commodity type in the matching warehouse is obtained.

[0026] Further, the quantity of goods is subtracted from the stock quantity, and the difference between the two is taken as the remaining quantity of goods; then it is determined whether the remaining quantity of goods is greater than or equal to the emergency quantity threshold of the matching warehouse, wherein the emergency quantity threshold can be set according to the real-time supply scenario of the matching warehouse. This threshold is usually to ensure that the warehouse can still meet subsequent demand after processing the current stock demand, and avoid the warehouse being unable to cope with sudden orders or demand fluctuations due to low inventory. If the remaining quantity of goods is greater than or equal to the emergency quantity threshold, the storage constraint is met, that is, the goods scheduling can continue.

[0027] If the remaining quantity of goods is less than the emergency quantity threshold of goods, the storage constraint is not met, that is, the current matching warehouse cannot meet the stocking demand and must be replenished through other warehouses. Then obtain the quantity of goods in multiple other warehouses, calculate multiple remaining quantities of goods, and select warehouses with remaining quantities greater than the emergency quantity threshold of goods (each warehouse contains an emergency quantity threshold) as support warehouses to obtain multiple support warehouses. Finally, obtain the quantity of goods in the multiple support warehouses to obtain multiple distributed quantities of goods. By obtaining multiple distributed quantities of goods, data support is provided for the next step of cargo scheduling plan analysis.

[0028] S200: Analyze and obtain multiple average cross-border cargo transfer times and multiple cross-border cargo transfer time floating parameters according to the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses, and compensate and obtain multiple floating cross-border cargo transfer times.

[0029] Furthermore, step S200 of the present invention further includes:

[0030] S210: Acquire multiple historical cross-border cargo transfer time sets according to the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses.

[0031] Specifically, the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses are queried, and multiple historical cargo transfer times for cargo dispatch by each supporting warehouse are collected based on the historical cargo dispatch records to obtain multiple historical cross-border cargo transfer time sets, wherein each supporting warehouse corresponds to a historical cross-border cargo transfer time set.

[0032] S220: Analyze and obtain a first average cross-border cargo transfer time and a first cross-border cargo transfer time floating parameter based on a first historical cross-border cargo transfer time set of the matching warehouse and the first supporting warehouse.

[0033] Further, step S220 of the present invention further includes:

[0034] S221: Calculate the mean of the first historical cross-border cargo transfer time set to obtain the first average cross-border cargo transfer time; S222: Randomly select two first historical cross-border cargo transfer times in the first historical cross-border cargo transfer time set, calculate the deviation ratio, and obtain a random time floating parameter; S223: Continue to randomly select multiple groups of first historical cross-border cargo transfer times, calculate multiple random time floating parameters, and calculate the mean to obtain the first cross-border cargo transfer time floating parameter.

[0035] Specifically, first, any one support warehouse is randomly selected from the multiple support warehouses as the first support warehouse, and a first historical cross-border transfer time set of the matching warehouse and the first support warehouse is obtained; then, the average of multiple transfer times in the first historical cross-border transfer time set is calculated, and the average calculation result is used as the first average cross-border transfer time.

[0036] Then, any two first historical cross-border cargo transfer times are randomly selected from the first historical cross-border cargo transfer time set, and the deviation ratio of the any two first historical cross-border cargo transfer times is calculated, wherein the deviation ratio is the ratio of the absolute value of the difference between the two to the maximum value between the two. For example, assuming that any two first historical cross-border cargo transfer times are 20 hours and 18 hours respectively, the deviation ratio is (20-18) / 20=10%; then the deviation ratio is set as the random time floating parameter. Further using the same method, continue to randomly select multiple groups of first historical cross-border cargo transfer times from the first historical cross-border cargo transfer time set, and calculate the deviation ratio of each group, until any group of data in the first historical cross-border cargo transfer time set is selected once, and multiple random time floating parameters are obtained; then the mean of the multiple random time floating parameters is calculated, and the mean calculation result is set as the first cross-border cargo transfer time floating parameter, the first cross-border cargo transfer time floating parameter represents the time fluctuation range of the first support warehouse transfer, and is used to reflect the uncertainty and volatility of the transfer time of the first support warehouse.

[0037] S230: Take the sum of the first cross-border cargo transfer time floating parameter and 1, multiply it by the first average cross-border cargo transfer time, and compensate to obtain the first floating cross-border cargo transfer time; S240: Continue to analyze and obtain multiple average cross-border cargo transfer times and multiple cross-border cargo transfer time floating parameters based on other multiple historical cross-border cargo transfer time sets, and compensate to obtain multiple floating cross-border cargo transfer times.

[0038] Specifically, the first cross-border cargo transfer time floating parameter and 1 are added together, and the sum of the two is multiplied by the first average cross-border cargo transfer time to compensate for the first average cross-border cargo transfer time, and the compensated first floating cross-border cargo transfer time is obtained. For example, assuming that the first cross-border cargo transfer time floating parameter is 20%, and the first average cross-border cargo transfer time is 30 hours, the first floating cross-border cargo transfer time is (1+0.2)*30=36 hours. By introducing floating parameters to compensate for cargo transfer time, the uncertainty of cargo transfer time caused by fluctuations in cargo transfer time (such as transportation delays, customs clearance issues, etc.) can be compensated, and the accuracy and reliability of the floating cross-border cargo transfer time setting can be improved.

[0039] Using the same method as that for calculating the first floating cross-border cargo transfer time, continue to analyze and obtain multiple average cross-border cargo transfer times and multiple cross-border cargo transfer time floating parameters based on multiple other historical cross-border cargo transfer time sets, and compensate the average cross-border cargo transfer time based on the cross-border cargo transfer time floating parameters to obtain multiple floating cross-border cargo transfer times, among which the floating cross-border cargo transfer times correspond one to one to the supporting warehouses.

[0040] S300: Based on the multiple floating cross-border transfer times and multiple distributed cargo quantities, and collecting the stocking frequencies of multiple warehouses, the warehouse joint control plan is optimized to obtain the optimal warehouse joint control plan, wherein the optimization is performed to reduce the cross-border transfer time, improve the balance of cargo quantities in multiple warehouses after the transfer, and reduce the total probability of cross-border transfer time between multiple warehouses after the transfer. The optimal warehouse joint control plan includes the optimal transfer support warehouse.

[0041] Furthermore, step S300 of the present invention further includes:

[0042] S310: Formulate multiple warehouse joint control plans based on the multiple supporting warehouses, wherein each warehouse joint control plan includes using different supporting warehouses to transfer goods to the matching warehouse according to the stocking demand; S320: Randomly select a first warehouse joint control plan from the multiple warehouse joint control plans, and obtain multiple remaining quantities of goods after transferring goods according to the first warehouse joint control plan, wherein the multiple remaining quantities of goods are calculated by subtracting the stocking quantity from the distributed quantity of goods in the supporting warehouses in the first warehouse joint control plan.

[0043] Specifically, first, according to the multiple supporting warehouses, a cargo dispatching plan is established for each supporting warehouse to transfer goods to the matching warehouse according to the stocking demand, and multiple storage joint control plans are obtained, wherein in each storage joint control plan, the matching warehouse and the supporting warehouse are in a one-to-one relationship. Then, any one of the multiple storage joint control plans is randomly selected as the first storage joint control plan, and multiple remaining cargo quantities after the transfer according to the first storage joint control plan are obtained, wherein only the cargo quantity of the supporting warehouse in the first storage joint control plan has changed, and the cargo quantity in other warehouses that have not transferred cargo remains unchanged, that is, the distributed cargo quantity of the supporting warehouse in the first storage joint control plan is subtracted from the stocking quantity, and the difference between the two is set as the remaining cargo quantity of the supporting warehouse in the first storage joint control plan, and the remaining cargo quantity after the transfer only affects the cargo quantity transferred in the supporting warehouse, and the cargo quantity in other supporting warehouses that have not participated in the transfer remains unchanged.

[0044] S330: Collecting the stocking frequencies of the multiple warehouses, combining the multiple remaining cargo quantities, analyzing and obtaining multiple first predicted cargo transfer probabilities and multiple first predicted floating cargo transfer times of the multiple supporting warehouses according to future preset time nodes.

[0045] Further, step S330 of the present invention further includes:

[0046] S331: According to the time length of the future preset time node, combined with the stocking frequency of the multiple warehouses, calculate and round up to obtain multiple first predicted stocking quantities; S332: Use the multiple remaining cargo quantities to subtract the multiple first predicted stocking quantities respectively, to obtain multiple first predicted cargo quantities; S333: Obtain multiple warehouse emergency cargo quantity thresholds of the multiple supporting warehouses, calculate the ratios of the multiple warehouse emergency cargo quantity thresholds to the multiple first predicted cargo quantities respectively, and obtain multiple first predicted cargo transfer probabilities; S334: Take the warehouse closest to each warehouse as the alternative cargo transfer support warehouse, combine the historical cargo scheduling records of each warehouse and the alternative cargo transfer support warehouse, and analyze to obtain multiple first predicted floating cargo transfer times.

[0047] Specifically, first, the stocking frequency of multiple warehouses is collected, where the stocking frequency refers to the stocking quantity of the warehouse within a certain period of time. For example, the stocking quantity is 50 pieces per day, which can be calculated based on historical stocking records. Next, configure the future preset time node, that is, a period of time in the future, which can be set according to the actual scenario, such as the next week. Further, based on the time length of the future preset time node and the stocking frequency of the multiple warehouses, the stocking quantity after the future preset time node is calculated, that is, the time length is multiplied by the stocking frequency, and the product of the two is rounded as the first predicted stocking quantity. For example, assuming that the future preset time node is 7 days and the stocking frequency is 50 pieces per day, the first predicted stocking quantity is 7*50=350 pieces, and multiple first predicted stocking quantities are obtained.

[0048] Next, the multiple remaining cargo quantities are subtracted from the multiple first predicted stock quantities, that is, the remaining cargo quantity corresponding to each support warehouse is subtracted from the first predicted stock quantity, and the difference between the two is taken as the first predicted cargo quantity to obtain multiple first predicted cargo quantities.

[0049] Further obtain multiple warehouse emergency cargo quantity thresholds of the multiple support warehouses, wherein each emergency cargo quantity threshold refers to the minimum inventory required for each warehouse to maintain normal operation within a certain period of time. This value is usually determined based on historical data, market demand, warehouse location, sales, and other factors. The warehouse emergency cargo quantity threshold of each support warehouse is different. For example, in areas with good business and large sales, the warehouse emergency cargo quantity threshold will be higher to cope with large demand fluctuations. Conversely, in areas with less sales, the warehouse threshold may be lower. Then calculate the ratio of the multiple warehouse emergency cargo quantity thresholds to the multiple first predicted cargo quantities, that is, calculate the ratio of the warehouse emergency cargo quantity threshold to the first predicted cargo quantity of the same support warehouse, and set the ratio of the two as the first predicted cargo transfer probability, and obtain multiple first predicted cargo transfer probabilities, wherein the first predicted cargo transfer probability is used to measure the cargo transfer probability of each warehouse after a preset time node in the future. The larger the cargo transfer probability, the more likely it is that the warehouse inventory is insufficient to meet future demand, and the higher the instability and volatility of the supply chain.

[0050] Then, the warehouse closest to each support warehouse (with the shortest transportation distance) is used as the alternative cargo transfer support warehouse, and the floating cargo transfer time is calculated based on the historical cargo dispatch records of each support warehouse and the alternative support warehouse, to obtain multiple first predicted floating cargo transfer times, wherein the calculation method of the first predicted floating cargo transfer time is the same as the calculation method of the above-mentioned floating cross-border cargo transfer time, that is, the mean of the alternative cargo transfer time and the floating parameters of the alternative cargo transfer time are calculated, and the alternative cargo transfer time is compensated for the mean of the alternative cargo transfer time using the floating parameters of the alternative cargo transfer time.

[0051] S340: Calculate and obtain the first joint control fitness of the first warehousing joint control scheme according to the multiple floating cross-border transfer times, the multiple remaining cargo quantities, the multiple first predicted transfer probabilities, and the multiple first predicted floating transfer times.

[0052] Further, step S340 of the present invention further includes:

[0053] S341: as follows: Among them, FITlk is the joint control fitness, w1, w2 and w3 are weights, T r is the floating cross-border transfer time between the supporting warehouse and the matching warehouse in the first warehouse joint control solution, T y is the historical average transfer time, N is the number of warehouses, S1 and S N are the remaining quantities of goods in the 1st and Nth warehouses respectively, and are the emergency goods quantity thresholds of the 1st and Nth warehouses, VAR is the variance, K iis the first predicted transfer probability of the i-th warehouse, T i is the first predicted floating transfer time of the i-th warehouse.

[0054] Specifically, firstly, with the comprehensive optimization purpose of reducing cross-border transfer time, improving the balance of goods quantity in multiple warehouses after transfer, and reducing the total probability of cross-border transfer time between multiple warehouses after transfer, the joint control fitness evaluation function of the warehouse joint control scheme is constructed. In the joint control fitness evaluation function, FITlk is the joint control fitness. The greater the joint control fitness, the better the overall effect of the scheme; w1, w2 and w3 are the weights of cross-border transfer time, warehouse goods balance, and total probability of cross-border transfer time, respectively. Among them, the sum of w1, w2 and w3 is 1. It can be set according to the degree of influence of the indicator on the overall joint control fitness. The greater the degree of influence, the greater the corresponding weight, for example, 0.4, 0.3 and 0.4 respectively. ; T r is the floating cross-border transfer time between the supporting warehouse and the matching warehouse in the first warehouse joint control solution, T y is the historical average transfer time; N is the number of warehouses, S1 and S N are the remaining quantities of goods in the 1st and Nth warehouses respectively, and are the emergency cargo quantity thresholds of the first and Nth warehouses, respectively. VAR is the variance, that is, the smaller the variance, the better the balance of cargo quantity in multiple warehouses after the transfer. K i is the first predicted transfer probability of the i-th warehouse, T i is the first predicted floating transfer time of the i-th warehouse.

[0055] Then, the joint control fitness evaluation function is used to calculate the first joint control fitness of the first warehousing joint control scheme according to the multiple floating cross-border transfer times, the multiple remaining cargo quantities, the multiple first predicted transfer probabilities, and the multiple first predicted floating transfer times.

[0056] S350: Continue to perform traversal optimization on the multiple warehouse joint control schemes, output the warehouse joint control scheme with the largest joint control fitness, and obtain the optimal warehouse joint control scheme.

[0057] Specifically, the same method for calculating the first joint control fitness is then used to continue calculating the joint control fitness of other warehousing joint control schemes in the multiple warehousing joint control schemes to obtain multiple joint control fitness of the multiple warehousing joint control schemes. Finally, the warehousing joint control scheme with the largest joint control fitness is selected as the optimal warehousing joint control scheme, and the supporting warehouse in the optimal warehousing joint control scheme is set as the optimal goods transfer supporting warehouse.

[0058] S400: adopting the optimal warehouse joint control solution to manage the transfer of goods from the optimal goods transfer support warehouse to the matching warehouse according to the stocking demand.

[0059] Specifically, the optimal warehouse joint control plan is finally adopted to transfer goods from the optimal transfer support warehouse to the matching warehouse on the condition of meeting the stocking demand.

[0060] The method for joint control and management of stocking warehouse for cross-border e-commerce provided by the embodiment of the present invention has at least the following technical effects:

[0061] By optimizing and analyzing the warehouse joint control plan with the comprehensive optimization purpose of reducing cross-border transfer time, improving the balance of goods quantity in multiple warehouses after transfer, and reducing the total probability of cross-border transfer time between multiple warehouses after transfer, the optimal warehouse joint control plan is obtained for transfer management, which can improve the flexibility, comprehensiveness and accuracy of cargo scheduling strategy setting. It can not only effectively reduce cross-border transfer time, but also improve inventory balance, reduce inventory backlogs and reduce supply chain fluctuations, realize efficient and accurate cross-border cargo scheduling, and significantly improve resource utilization and overall operational efficiency.

[0062] Embodiment 2, as Figure 2 As shown, based on the same inventive concept as the method for joint control of stocking and warehousing for cross-border e-commerce provided in Example 1, the embodiment of the present invention also provides a joint control management platform for stocking and warehousing for cross-border e-commerce, including:

[0063] The stocking demand analysis module 01 is used to respond to the current stocking demand. When the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the storage constraints, multiple distributed quantities of goods in other multiple supporting warehouses are obtained, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations; the floating cross-border transfer time acquisition module 02 is used to analyze and obtain multiple average cross-border transfer times and multiple cross-border transfer time floating parameters based on the historical cargo scheduling records of the matching warehouse and the multiple supporting warehouses, and compensate to obtain multiple floating cross-border transfer times; the warehouse joint control solution optimization module 03, used to optimize the warehouse joint control plan according to the multiple floating cross-border transfer times and multiple distributed cargo quantities, and collect the stocking frequency of multiple warehouses to obtain the optimal warehouse joint control plan, wherein the optimization is performed to reduce the cross-border transfer time, improve the balance of cargo quantities in multiple warehouses after the transfer, and reduce the total probability of cross-border transfer time between multiple warehouses after the transfer. The optimal warehouse joint control plan includes an optimal transfer support warehouse; the transfer management module 04 is used to adopt the optimal warehouse joint control plan to manage the transfer from the optimal transfer support warehouse to the matching warehouse according to the stocking demand.

[0064] Furthermore, the stocking warehouse joint control management platform for cross-border e-commerce also includes: in response to the current stocking demand, obtaining the stocking quantity and stocking address within the stocking demand; according to the stocking address, matching the nearest warehouse among multiple warehouses as a matching warehouse, and obtaining the quantity of goods in the matching warehouse, wherein the multiple warehouses are distributed in multiple locations; subtracting the stocking quantity from the quantity of goods to obtain the remaining quantity of goods, and judging whether the remaining quantity of goods is greater than or equal to the emergency quantity threshold of the matching warehouse, if so, the storage constraint is met, if not, the storage constraint is not met; when the storage constraint is not met, obtaining the quantity of goods in other multiple warehouses, and obtaining multiple supporting warehouses that meet the storage constraint based on the calculation of the stocking quantity, and obtaining the quantity of goods in the multiple supporting warehouses as multiple distributed quantity of goods.

[0065] Furthermore, the inventory storage joint control management platform for cross-border e-commerce also includes: obtaining multiple historical cross-border transfer time sets based on the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses; analyzing and obtaining the first average cross-border transfer time and the first cross-border transfer time floating parameter based on the first historical cross-border transfer time set of the matching warehouse and the first supporting warehouse; taking the sum of the first cross-border transfer time floating parameter and 1, multiplying it by the first average cross-border transfer time, and compensating to obtain the first floating cross-border transfer time; continuing to analyze and obtain multiple average cross-border transfer times and multiple cross-border transfer time floating parameters based on other multiple historical cross-border transfer time sets, and compensating to obtain multiple floating cross-border transfer times.

[0066] Furthermore, the inventory warehousing joint control management platform for cross-border e-commerce also includes: calculating the mean of the first historical cross-border transfer time set to obtain a first average cross-border transfer time; randomly selecting two first historical cross-border transfer times in the first historical cross-border transfer time set, calculating the deviation ratio, and obtaining a random time floating parameter; continuing to randomly select multiple groups of first historical cross-border transfer times, calculating multiple random time floating parameters, and calculating the mean to obtain the first cross-border transfer time floating parameter.

[0067] Further, the stocking warehouse joint control management platform for cross-border e-commerce also includes: formulating multiple storage joint control plans based on the multiple supporting warehouses, wherein each storage joint control plan includes using different supporting warehouses to transfer goods to the matching warehouse according to the stocking demand; randomly selecting a first storage joint control plan from the multiple storage joint control plans, and obtaining multiple remaining goods quantities after transferring goods according to the first storage joint control plan, wherein the distributed goods quantity of the supporting warehouse in the first storage joint control plan is subtracted from the stocking quantity to calculate the multiple remaining goods quantities; collecting the stocking frequencies of multiple warehouses, combining the multiple remaining goods quantities, analyzing and obtaining multiple first predicted stocking probabilities and multiple first predicted floating stocking times of the multiple supporting warehouses according to future preset time nodes; calculating and obtaining the first joint control fitness of the first storage joint control plan according to the multiple floating cross-border stocking times, the multiple remaining goods quantities, the multiple first predicted stocking probabilities, and the multiple first predicted floating stocking times; continuing to perform traversal optimization of the storage joint control plans among the multiple storage joint control plans, outputting the storage joint control plan with the largest joint control fitness, and obtaining the optimal storage joint control plan.

[0068] Furthermore, the stocking warehousing joint control management platform for cross-border e-commerce also includes: according to the time length of the future preset time node, combined with the stocking frequency of the multiple warehouses, calculating and rounding to obtain multiple first predicted stocking quantities; respectively using the multiple remaining cargo quantities minus the multiple first predicted stocking quantities to obtain multiple first predicted cargo quantities; obtaining multiple warehouse emergency cargo quantity thresholds of the multiple supporting warehouses, respectively calculating the ratios of the multiple warehouse emergency cargo quantity thresholds to the multiple first predicted cargo quantities, to obtain multiple first predicted cargo transfer probabilities; taking the warehouse closest to each warehouse as an alternative cargo transfer support warehouse, combining the historical cargo scheduling records of each warehouse and the alternative cargo transfer support warehouse, and analyzing to obtain multiple first predicted floating cargo transfer times.

[0069] Furthermore, the inventory storage joint control management platform for cross-border e-commerce further includes: calculating the first joint control fitness of the first warehousing joint control scheme according to the multiple floating cross-border transfer times, the multiple remaining goods quantities, the multiple first predicted transfer probabilities, and the multiple first predicted floating transfer times, as shown in the following formula: Among them, FITlk is the joint control fitness, w1, w2 and w3 are weights, T r is the floating cross-border transfer time between the supporting warehouse and the matching warehouse in the first warehouse joint control solution, T y is the historical average transfer time, N is the number of warehouses, S1 and S N are the remaining quantities of goods in the 1st and Nth warehouses respectively, and are the emergency goods quantity thresholds of the 1st and Nth warehouses, VAR is the variance, K i is the first predicted transfer probability of the i-th warehouse, T i is the first predicted floating transfer time of the i-th warehouse.

[0070] For example 3, please refer to Figure 3 , Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 500, including a memory 510, a processor 520, and a first computer program 511 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the first computer program 511, the following steps are implemented: in response to the current stocking demand, when the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the storage constraint, obtaining multiple distributed quantities of goods in other multiple supporting warehouses, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations; according to the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses, analyzing and obtaining multiple The average cross-border transfer time and multiple cross-border transfer time floating parameters are used to compensate for multiple floating cross-border transfer times; based on the multiple floating cross-border transfer times and multiple distributed cargo quantities, and collecting the stocking frequency of multiple warehouses, the warehousing joint control plan is optimized to obtain the optimal warehousing joint control plan, wherein the cross-border transfer time is reduced, the quantity balance of goods in multiple warehouses after the transfer is improved, and the total probability of cross-border transfer time between multiple warehouses after the transfer is reduced. The optimal warehousing joint control plan includes an optimal transfer support warehouse; the optimal warehousing joint control plan is used to manage the transfer of goods from the optimal transfer support warehouse to the matching warehouse according to the stocking demand.

[0071] Example 4, please refer to Figure 4 , Figure 4 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 4As shown, this embodiment provides a computer-readable storage medium 600, on which a second computer program 611 is stored. When the second computer program 611 is executed by a processor, the following steps are implemented: in response to the current stocking demand, when the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the storage constraint, obtain multiple distributed quantities of goods in other multiple supporting warehouses, wherein the matching warehouse and the multiple supporting warehouses are distributed in multiple cross-border locations; according to the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses, analyze and obtain multiple average cross-border transfer times and multiple cross-border transfer times The floating parameters are compensated to obtain multiple floating cross-border transfer times; according to the multiple floating cross-border transfer times and multiple distributed cargo quantities, and the stocking frequency of multiple warehouses is collected, the warehousing joint control plan is optimized to obtain the optimal warehousing joint control plan, wherein the cross-border transfer time is optimized to reduce the cross-border transfer time, improve the balance of cargo quantities in multiple warehouses after the transfer, and reduce the total probability of cross-border transfer time between multiple warehouses after the transfer, and the optimal warehousing joint control plan includes an optimal transfer support warehouse; the optimal warehousing joint control plan is adopted to manage the transfer of goods from the optimal transfer support warehouse to the matching warehouse according to the stocking demand.

[0072] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0073] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product 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.

[0074] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0077] Although preferred embodiments of the present invention have been described, additional changes and modifications may occur to these embodiments once those skilled in the art understand the basic inventive concepts.

[0078] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the present invention and its equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A method for joint control and management of stocking warehouse for cross-border e-commerce, characterized in that: Methods include: In response to a current stocking demand, when the quantity of goods in a matching warehouse corresponding to the stocking demand does not satisfy a storage constraint, obtaining a plurality of distributed quantities of goods in other plurality of supporting warehouses, wherein the matching warehouse and the plurality of supporting warehouses are distributed in a plurality of cross-border locations; According to the historical cargo dispatch records of the matching warehouse and the plurality of supporting warehouses, a plurality of average cross-border cargo transfer times and a plurality of floating parameters of cross-border cargo transfer times are obtained by analysis, and a plurality of floating cross-border cargo transfer times are obtained by compensation; According to the multiple floating cross-border transfer times and the multiple distributed cargo quantities, and collecting the stocking frequencies of multiple warehouses, the warehouse joint control plan is optimized to obtain the optimal warehouse joint control plan, wherein the optimization is performed by reducing the cross-border transfer time, improving the balance of the cargo quantities in multiple warehouses after the transfer, and reducing the total probability of cross-border transfer time between multiple warehouses after the transfer, and the optimal warehouse joint control plan includes the optimal transfer support warehouse; The optimal warehouse joint control solution is adopted to manage the transfer of goods from the optimal transfer support warehouse to the matching warehouse according to the stocking demand.

2. The method for joint control and management of stocking warehouse for cross-border e-commerce according to claim 1 is characterized in that: In response to the current stocking demand, when the quantity of goods in the matching warehouse corresponding to the stocking demand does not meet the storage constraint, multiple distributed quantities of goods in other multiple supporting warehouses are obtained, including: In response to the current stocking demand, obtaining the stocking quantity and stocking address in the stocking demand; According to the stocking address, a warehouse closest to the multiple warehouses is matched as a matching warehouse, and the quantity of goods in the matching warehouse is obtained, wherein the multiple warehouses are distributed in multiple locations; The remaining quantity of goods is obtained by subtracting the stock quantity from the quantity of goods, and it is determined whether the remaining quantity of goods is greater than or equal to the emergency quantity threshold of the matching warehouse. If so, the storage constraint is met; otherwise, the storage constraint is not met; When the storage constraints are not met, the quantity of goods in other multiple warehouses is obtained, and multiple supporting warehouses that meet the storage constraints are obtained based on the calculation and judgment of the stock quantity, and the quantity of goods in the multiple supporting warehouses is obtained as multiple distributed goods quantities.

3. The method for joint control and management of stocking warehouse for cross-border e-commerce according to claim 1 is characterized in that: According to the historical cargo dispatch records of the matching warehouse and the plurality of supporting warehouses, a plurality of average cross-border cargo transfer times and a plurality of floating parameters of cross-border cargo transfer times are obtained through analysis, and a plurality of floating cross-border cargo transfer times are obtained through compensation, including: Acquire multiple historical cross-border cargo transfer time sets according to the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses; Analyze and obtain a first average cross-border cargo transfer time and a first cross-border cargo transfer time floating parameter based on a first historical cross-border cargo transfer time set of the matching warehouse and the first supporting warehouse; The sum of the first cross-border goods transfer time floating parameter and 1 is multiplied by the first average cross-border goods transfer time, and a first floating cross-border goods transfer time is obtained through compensation processing; Continue to analyze and obtain multiple average cross-border transfer times and multiple cross-border transfer time floating parameters based on other multiple historical cross-border transfer time sets, and compensate to obtain multiple floating cross-border transfer times.

4. The method for joint control and management of stocking warehouse for cross-border e-commerce according to claim 3 is characterized in that: According to the first historical cross-border transfer time set of the matching warehouse and the first supporting warehouse, a first average cross-border transfer time and a first cross-border transfer time floating parameter are obtained by analysis, including: Calculate the mean of the first historical cross-border goods transfer time set to obtain a first average cross-border goods transfer time; Randomly select two first historical cross-border cargo transfer times from the first historical cross-border cargo transfer time set, calculate the deviation ratio, and obtain a random time floating parameter; Continue to randomly extract multiple groups of the first historical cross-border transfer time, calculate multiple random time floating parameters, and calculate the mean to obtain the first cross-border transfer time floating parameter.

5. The method for joint control and management of stocking warehouse for cross-border e-commerce according to claim 1 is characterized in that: According to the multiple floating cross-border transfer times and multiple distributed cargo quantities, and collecting the stocking frequencies of multiple warehouses, the warehouse joint control plan is optimized to obtain the optimal warehouse joint control plan, including: Formulate multiple warehouse joint control plans based on the multiple supporting warehouses, wherein each warehouse joint control plan includes using different supporting warehouses to transfer goods to the matching warehouse according to the stocking demand; Randomly selecting a first warehousing joint control scheme from the multiple warehousing joint control schemes, and obtaining multiple quantities of remaining goods after adjusting goods according to the first warehousing joint control scheme, wherein the multiple quantities of remaining goods are calculated by subtracting the quantity of stocked goods from the quantity of distributed goods in the support warehouse within the first warehousing joint control scheme; Collecting the stocking frequencies of the multiple warehouses, combining the multiple remaining goods quantities, analyzing and obtaining multiple first predicted stock transfer probabilities and multiple first predicted floating stock transfer times of the multiple supporting warehouses according to future preset time nodes; Calculate and obtain the first joint control fitness of the first warehousing joint control scheme according to the multiple floating cross-border cargo transfer times, the multiple remaining cargo quantities, the multiple first predicted cargo transfer probabilities, and the multiple first predicted floating cargo transfer times; Continue to perform traversal optimization on the multiple warehouse joint control schemes, output the warehouse joint control scheme with the largest joint control fitness, and obtain the optimal warehouse joint control scheme.

6. The method for joint control and management of stocking warehouse for cross-border e-commerce according to claim 5 is characterized in that: Collecting the stocking frequencies of multiple warehouses, combining the multiple remaining goods quantities, analyzing and obtaining multiple first predicted stock transfer probabilities and multiple first predicted floating stock transfer times of the multiple supporting warehouses according to future preset time nodes, including: According to the time length of the future preset time node and the stocking frequency of the multiple warehouses, multiple first predicted stocking quantities are calculated and rounded to obtain; Subtracting the plurality of first predicted stock quantities from the plurality of remaining goods quantities respectively to obtain a plurality of first predicted goods quantities; Acquire multiple warehouse emergency cargo quantity thresholds of the multiple support warehouses, calculate ratios of the multiple warehouse emergency cargo quantity thresholds to the multiple first predicted cargo quantities, and obtain multiple first predicted cargo transfer probabilities; The warehouse closest to each warehouse is used as an alternative cargo transfer support warehouse, and the historical cargo scheduling records of each warehouse and the alternative cargo transfer support warehouse are combined to analyze and obtain multiple first predicted floating cargo transfer times.

7. The method for joint control and management of stocking warehouse for cross-border e-commerce according to claim 6 is characterized in that: According to the multiple floating cross-border transfer times, the multiple remaining cargo quantities, the multiple first predicted transfer probabilities, and the multiple first predicted floating transfer times, the first joint control fitness of the first warehousing joint control scheme is calculated as follows: Among them, FITlk is the joint control fitness, w1, w2 and w3 are weights, T r is the floating cross-border transfer time between the supporting warehouse and the matching warehouse in the first warehouse joint control solution, T y is the historical average transfer time, N is the number of warehouses, S1 and S N are the remaining quantities of goods in the 1st and Nth warehouses respectively, and are the emergency goods quantity thresholds of the 1st and Nth warehouses, VAR is the variance, K i is the first predicted transfer probability of the i-th warehouse, T i is the first predicted floating transfer time of the i-th warehouse.

8. The stocking warehouse joint control management platform for cross-border e-commerce is characterized by: The steps for implementing the method for joint control of stocking and warehousing for cross-border e-commerce according to any one of claims 1 to 7 include: A stocking demand analysis module, configured to, in response to a current stocking demand, obtain a plurality of distributed quantities of goods in a plurality of other supporting warehouses when the quantity of goods in the matching warehouse corresponding to the stocking demand does not satisfy a storage constraint, wherein the matching warehouse and the plurality of supporting warehouses are distributed in a plurality of cross-border locations; A floating cross-border cargo transfer time acquisition module is used to analyze and obtain multiple average cross-border cargo transfer times and multiple cross-border cargo transfer time floating parameters according to the historical cargo dispatch records of the matching warehouse and the multiple supporting warehouses, and compensate to obtain multiple floating cross-border cargo transfer times; A warehouse joint control scheme optimization module is used to optimize the warehouse joint control scheme according to the multiple floating cross-border transfer times and the multiple distributed cargo quantities, and collect the stocking frequencies of multiple warehouses to obtain the optimal warehouse joint control scheme, wherein the optimization is performed by reducing the cross-border transfer time, improving the balance of cargo quantities in multiple warehouses after the transfer, and reducing the total probability of cross-border transfer time between multiple warehouses after the transfer, and the optimal warehouse joint control scheme includes the optimal transfer support warehouse; The goods transfer management module is used to adopt the optimal warehouse joint control solution to manage the transfer of goods from the optimal goods transfer support warehouse to the matching warehouse according to the stocking demand.

9. An electronic device, characterized in that: include: Memory for storing computer software programs; A processor is used to read and execute the computer software program, thereby implementing the steps of the method for joint control of inventory storage for cross-border e-commerce as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores a computer software program, which, when executed by a processor, implements the steps of the method for joint control of inventory storage for cross-border e-commerce as described in any one of claims 1 to 7.

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