A warehouse and logistics matching method and system for e-commerce orders

Abstract

The application discloses a warehouse and logistics matching method and system for e-commerce orders, relates to the technical field of warehouse and logistics matching for e-commerce orders, and comprises the following steps: acquiring warehouse and logistics basic data; configuring a matching rule based on the warehouse and logistics basic data; acquiring to-be-processed order data; performing warehouse and logistics matching according to the to-be-processed order data and the matching rule, and determining an optimal warehouse-logistics combination; and the optimal warehouse-logistics combination is a warehouse-logistics combination with the lowest comprehensive cost. The application can realize accurate matching of warehouses and logistics after e-commerce order splitting, reduce logistics cost, and improve the operation efficiency and economic benefits of e-commerce.

Description

Technical Field

[0001] This application relates to the field of e-commerce order warehousing and logistics matching technology, and in particular to a method and system for matching e-commerce orders with warehousing and logistics. Background Technology

[0002] In the complex operational scenarios of e-commerce with multiple warehouses and logistics, merchants often face the challenge of optimizing costs after order splitting when using order management systems. The traditional method uses warehouse priority rules, mechanically pushing orders based on the priority values ​​set when configuring warehouses for the store. This approach has significant drawbacks: even if low-cost warehouses have sufficient inventory, orders will still be concentrated in high-cost warehouses, leading to a mismatch between warehouse and logistics, ultimately resulting in high logistics costs. Furthermore, manual intervention for secondary splitting and repackaging is extremely inefficient, and in the after-sales process, order traceability is severely hampered because consumers cannot perceive the order splitting. These problems seriously impact e-commerce operational efficiency and economic benefits. Therefore, there is an urgent need to design a method and system for matching e-commerce orders with warehouses and logistics to achieve accurate matching after order splitting, reduce logistics costs, and improve e-commerce operational efficiency and economic benefits. Summary of the Invention

[0003] The purpose of this application is to provide a method and system for matching warehouses and logistics for e-commerce orders, which can achieve accurate matching of warehouses and logistics after e-commerce orders are split, reduce logistics costs, and improve the operational efficiency and economic benefits of e-commerce.

[0004] To achieve the above objectives, this application provides the following solution.

[0005] In a first aspect, this application provides a method for matching warehouses and logistics for e-commerce orders, which includes the following steps.

[0006] Acquire basic warehouse and logistics data; the basic warehouse and logistics data includes: basic warehouse data, basic logistics data, warehouse-logistics related data, cost surcharge data, and strategy activation control data.

[0007] Based on the aforementioned warehouse and logistics data, matching rules are configured. The configuration parameters of the matching rules include: selectable logistics range, backup warehouse set, alternative warehouse set, fixed cost markup for each warehouse, and warehouse-logistics relationship.

[0008] Obtain pending order data; the pending order data includes: receiving store, product details, delivery address and customer service remarks.

[0009] Based on the pending order data and the matching rules, warehouses and logistics are matched to determine the optimal warehouse-logistics combination; the optimal warehouse-logistics combination is the warehouse-logistics combination with the lowest overall cost.

[0010] Optionally, the warehouse basic data includes: warehouse identification information, warehouse functional attributes, and warehouse basic status; the logistics basic data includes: logistics entity information, logistics billing parameters, and logistics service scope; the warehouse-logistics association data includes: the optional logistics list corresponding to each optional warehouse in the candidate warehouse set and the associated logistics list corresponding to each backup warehouse in the backup warehouse set; the cost surcharge data includes: the fixed cost surcharge amount corresponding to each of the candidate warehouses and the backup warehouse; the strategy activation control data includes: strategy activation method and optional logistics scope limitation data.

[0011] Optionally, based on the warehouse and logistics basic data, matching rules are configured, specifically including the following steps.

[0012] Enable warehouse-level association mode for logistics matching.

[0013] Based on the warehouse dimension association mode of the logistics matching, according to the warehouse basic data, the logistics basic data and the warehouse-logistics association data, the corresponding logistics cost information is maintained according to the warehouse dimension, and the warehouse-logistics association relationship is automatically established and identified.

[0014] Based on the cost surcharge data, the strategy activation control data, and the warehouse-logistics relationship, a "select warehouse and logistics by tariff" strategy is added to the order processing flow settings. The activation attribute of the "select warehouse and logistics by tariff" strategy is configured, a fallback warehouse set, a backup warehouse set, and fixed cost surcharge parameters for each warehouse are set, and the range of selectable logistics is defined. If the range of selectable logistics is not defined, all logistics are included in the selectable range by default.

[0015] Optionally, the logistics pricing information includes: pricing identification information, logistics service provider information, logistics service type, service activation status, activation period, billing rules, service coverage area, fixed surcharge amount, initial weight threshold, initial weight fee, subsequent weight unit and subsequent weight fee.

[0016] Optionally, the activation attribute includes: policy-based immediate activation or timed activation. When configuring timed activation, a specific activation time node needs to be set.

[0017] Optionally, warehouse and logistics matching is performed based on the order data to be processed and the matching rules to determine the optimal warehouse-logistics combination, specifically including the following steps.

[0018] Based on the order data to be processed and the matching rules, the inventory validity of each candidate warehouse in the candidate warehouse set is checked in turn, and the target warehouse whose inventory meets the order requirements is selected.

[0019] Calculate the comprehensive cost of logistics associated with each of the target warehouses, and sort the comprehensive costs to obtain the cost ranking result; the comprehensive cost is the sum of the basic logistics cost and the corresponding warehouse fixed cost surcharge parameter.

[0020] The uniqueness of the lowest comprehensive fee is determined based on the fee ranking results. If there are multiple warehouse-logistics combinations with the same lowest comprehensive fee, the optimal warehouse-logistics combination is selected based on the geographical distance between the receiving address in the pending order data and each of the target warehouses. If the lowest comprehensive fee is unique, the warehouse-logistics combination corresponding to the lowest comprehensive fee is directly determined as the optimal warehouse-logistics combination.

[0021] If none of the candidate warehouses in the candidate warehouse set meet the inventory requirements, the fallback warehouse in the fallback warehouse set will be automatically activated. The inventory of the fallback warehouse will not be checked. The logistics with the lowest cost will be selected from the logistics associated with the fallback warehouse as the order logistics. If there is no associated logistics, the order logistics information will be left blank to obtain the optimal warehouse-logistics combination.

[0022] Optionally, the optimal warehouse-logistics combination is selected based on the delivery address in the order data to be processed and the geographical distance of each of the target warehouses, specifically including the following steps.

[0023] The geographical distances between the receiving addresses in the order data to be processed and each of the target warehouses are calculated to obtain multiple geographical distance values.

[0024] The target warehouse corresponding to the smallest geographical distance value among the multiple geographical distance values ​​is selected as the warehouse to obtain the optimal warehouse-logistics combination.

[0025] Optionally, after the step of selecting the logistics with the lowest cost from the logistics associated with the backup warehouse as the order logistics, the warehouse and logistics matching method for e-commerce orders further includes the following steps.

[0026] Configure a primary and secondary logistics matching mechanism; the primary and secondary logistics matching mechanism means that when the selected logistics is the primary logistics, the secondary logistics corresponding to the platform to which the order belongs is automatically matched to ensure the normal fulfillment of the order; the primary logistics is the logistics of the baseline logistics type manually selected by the user when maintaining the logistics type of a certain logistics company; the secondary logistics is the logistics of the platform-specific logistics type that belongs to the same logistics company as the primary logistics but corresponds to a different e-commerce platform.

[0027] Optionally, when determining the uniqueness of the lowest comprehensive tariff, a tariff difference threshold is preset. When the comprehensive tariff difference of different warehouse-logistics combinations is within the tariff difference threshold, it is determined that the lowest comprehensive tariff of the warehouse-logistics combination is the same.

[0028] Secondly, this application proposes a warehouse and logistics matching system for e-commerce orders. The warehouse and logistics matching system for e-commerce orders is used to implement the warehouse and logistics matching method for e-commerce orders described in the first aspect. The warehouse and logistics matching system for e-commerce orders includes the following modules.

[0029] The basic data acquisition module is used to acquire basic warehouse and logistics data; the basic warehouse and logistics data includes: basic warehouse data, basic logistics data, warehouse-logistics related data, cost surcharge data, and strategy activation control data.

[0030] The matching rule configuration module is used to configure matching rules based on the warehouse and logistics basic data. The configuration parameters of the matching rules include: optional logistics range, backup warehouse set, alternative warehouse set, fixed cost surcharge for each warehouse, and warehouse-logistics association.

[0031] The order data acquisition module is used to acquire order data to be processed; the order data to be processed includes: receiving store, product details, delivery address and customer service remarks.

[0032] The warehouse-logistics matching module is used to match warehouses and logistics based on the order data to be processed and the matching rules, and to determine the optimal warehouse-logistics combination; the optimal warehouse-logistics combination is the warehouse-logistics combination with the lowest overall cost.

[0033] According to the specific embodiments provided in this application, this application has the following technical effects.

[0034] This application provides a method and system for matching warehouses and logistics for e-commerce orders. It combines inventory status, fixed warehouse markups, and logistics costs to establish a dynamic decision-making mechanism to achieve warehouse and logistics matching and the selection of the optimal warehouse-logistics combination, thereby reducing logistics costs and improving the operational efficiency and economic benefits of e-commerce.

[0035] First, this application obtains warehouse-logistics correlation data and cost surcharge data, and configures matching rules such as fixed cost surcharges for each warehouse and warehouse-logistics correlation relationships based on this data, thus clarifying the logistics resources and overall cost structure corresponding to each warehouse. During the matching phase, the system can filter the warehouse-logistics combination with the lowest overall cost from the set of candidate warehouses and the range of available logistics based on the order data to be processed, reducing logistics costs and avoiding the problem of orders concentrating on high-cost warehouses under traditional fixed priority rules, which is beneficial to improving the economic efficiency of e-commerce. By configuring the range of available logistics in the matching rules, the selection can be limited to low-cost, high-performance logistics, further reducing the probability of selecting high-cost logistics, assisting in the overall logistics cost control, and further improving the economic efficiency of e-commerce. By pre-acquiring basic warehouse and logistics data and configuring standardized matching rules, subsequent order data can be automatically matched with warehouses and logistics based on preset rules, and the optimal combination can be selected. There is no need for manual comparison of warehouse-logistics resources, calculation of fees, or designation of shipping warehouses. This not only significantly shortens the time from order receipt to determining the warehousing and distribution plan and improves the efficiency of warehouse and logistics matching, thereby improving the operational efficiency of e-commerce, but also eliminates the errors of manual calculation, achieving accurate matching of warehouses and logistics after e-commerce order splitting, and improving the accuracy of warehouse and logistics matching.

[0036] Secondly, this application clearly defines the backup warehouse set through the rule configuration phase. This design allows the system to automatically activate the backup warehouse and match its associated logistics when the alternative warehouses are out of stock, eliminating the need for manual intervention to handle order delays caused by insufficient inventory. This reduces manual intervention and improves the continuity and efficiency of order processing. By obtaining basic warehouse data to define the alternative and backup warehouse sets, a two-tiered guarantee mechanism is formed, prioritizing alternative warehouses and supplementing with backup warehouses. This avoids situations where orders cannot be allocated warehousing and distribution solutions due to stockouts in a single warehouse, improving order fulfillment rates. By establishing a clear warehouse-logistics correspondence based on warehouse-logistics association data through matching rules, and ensuring that the order data includes the delivery address, it is guaranteed that the selected logistics can cover the delivery area, avoiding fulfillment failures due to mismatched logistics service areas and reducing the risk of abnormal order fulfillment. By enabling the use of policy-based control data configuration matching rules, and flexibly defining the optional logistics range, alternative warehouse set, and backup warehouse set, it can adapt to the needs of e-commerce enterprises at different operational stages (such as adding alternative warehouses during major promotional periods and limiting high-efficiency logistics during holidays) and different regional orders (such as designating exclusive alternative warehouses for specific regions). There is no need to reconstruct the overall method; simply adjusting the rule configuration can quickly respond to changes in the scenario.

[0037] In addition, by setting customer service remarks in the pending order data, this application can adjust the matching logic during the matching process based on the special requirements in the remarks (such as specifying the logistics type or prioritizing delivery to a certain regional warehouse), thereby further improving the ability to adapt to personalized order requirements. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is an application environment diagram of a warehouse and logistics matching method for e-commerce orders provided in an embodiment of this application.

[0040] Figure 2 This is a flowchart illustrating a warehouse and logistics matching method for e-commerce orders, provided as an embodiment of this application.

[0041] Figure 3 This is a schematic diagram of a warehouse and logistics matching method for e-commerce orders provided in an embodiment of this application.

[0042] Figure 4 This is a schematic diagram of a warehouse dimension interface provided in one embodiment of this application.

[0043] Figure 5 This is a schematic diagram of the maintenance logistics fee interface provided in one embodiment of this application.

[0044] Figure 6 This is a schematic diagram of a warehouse and logistics selection interface based on pricing, provided as an embodiment of this application.

[0045] Figure 7 This is a schematic diagram of the interface for selecting the corresponding platform logistics through the main logistics provider, provided as an embodiment of this application.

[0046] Figure 8 This is a schematic diagram of the structure of an e-commerce order warehouse and logistics matching system provided in one embodiment of this application. Detailed Implementation

[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0048] The purpose of this application is to provide a method and system for matching warehouses and logistics for e-commerce orders. The core of this method is to combine inventory status, warehouse fixed markups, and logistics costs to establish a dynamic decision-making mechanism. After order splitting, the optimal warehouse-logistics combination is automatically selected, which can achieve accurate matching of warehouses and logistics after e-commerce order splitting, reduce logistics costs, and improve the operational efficiency and economic benefits of e-commerce.

[0049] 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.

[0050] The warehouse and logistics matching method for e-commerce orders provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on another server. Terminal 102 can send warehouse and logistics basic data and pending order data to server 104. After receiving the warehouse and logistics basic data and pending order data, server 104 configures matching rules based on the warehouse and logistics basic data; and performs warehouse and logistics matching according to the pending order data and the matching rules to determine the optimal warehouse-logistics combination. Server 104 can then feed back the obtained optimal warehouse-logistics combination to terminal 102. In addition, in some embodiments, the warehouse and logistics matching method for e-commerce orders can also be implemented separately by the server 104 or the terminal 102. For example, the terminal 102 can directly perform warehouse and logistics matching processing on the warehouse and logistics basic data and the order data to be processed, or the server 104 can obtain the warehouse and logistics basic data and the order data to be processed from the data storage system and perform warehouse and logistics matching processing on the warehouse and logistics basic data and the order data to be processed.

[0051] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, and IoT devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0052] In one exemplary embodiment, such as Figure 2 As shown, a method for matching warehouses and logistics for e-commerce orders is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1Taking server 104 as an example, the explanation includes the following steps S1 to S4.

[0053] S1: Obtain basic warehouse and logistics data. This basic warehouse and logistics data includes: basic warehouse data, basic logistics data, warehouse-logistics related data, cost surcharge data, and policy activation control data, etc.

[0054] S2: Based on the aforementioned warehouse and logistics data, configure matching rules. The configuration parameters for these matching rules include: selectable logistics range, fallback warehouse set, alternative warehouse set, fixed cost surcharges for each warehouse, and warehouse-logistics relationship, etc.

[0055] S3: Obtain pending order data. The pending order data includes: receiving store, product details, shipping address, and customer service remarks, etc.

[0056] S4: Based on the pending order data and the matching rules, perform warehouse and logistics matching to determine the optimal warehouse-logistics combination. The optimal warehouse-logistics combination is the one with the lowest overall cost.

[0057] By implementing steps S1 to S4 above, and acquiring warehouse-logistics association data and cost surcharge data, and configuring matching rules such as fixed cost surcharges for each warehouse and warehouse-logistics association relationships based on this data, the system can clearly define the logistics resources and overall cost structure corresponding to each warehouse. During the matching phase, the system can filter out the warehouse-logistics combination with the lowest overall cost from the set of candidate warehouses and the range of selectable logistics based on the order data to be processed. This reduces logistics costs and avoids the problem of orders concentrating on high-cost warehouses under traditional fixed priority rules, thus improving the economic efficiency of e-commerce. By configuring the range of selectable logistics in the matching rules, the system can limit the selection to low-cost, high-performance logistics, further reducing the probability of selecting high-cost logistics, assisting in overall logistics cost control, and further improving the economic efficiency of e-commerce. By pre-acquiring basic warehouse and logistics data and configuring standardized matching rules, the system can automatically match warehouses and logistics providers and select the optimal combination upon receiving order data. This eliminates the need for manual comparison of warehouse-logistics resources, calculation of fees, or designation of shipping warehouses. This significantly reduces the time from order receipt to determining a warehousing and distribution plan, improving the efficiency of warehouse and logistics matching and thus enhancing e-commerce operational efficiency. It also eliminates errors from manual calculations, achieving precise matching of warehouses and logistics after order splitting, thus improving the accuracy of warehouse and logistics matching. Furthermore, this application clearly defines a fallback warehouse set during the rule configuration phase. This design allows the system to automatically activate the fallback warehouse and match its associated logistics when the alternative warehouses are out of stock, eliminating the need for manual intervention to handle order delays caused by insufficient inventory. This reduces manual intervention steps and improves the continuity and efficiency of order processing. By acquiring basic warehouse data and clearly defining the alternative and fallback warehouse sets, a two-tiered guarantee mechanism of prioritizing alternative warehouses and supplementing with fallback warehouses is formed. This avoids situations where orders cannot be allocated warehousing and distribution plans due to stockouts in a single warehouse, improving order fulfillment rates. By establishing a clear warehouse-logistics correspondence based on warehouse-logistics association data through matching rules, and ensuring that the pending order data includes the delivery address, the selected logistics can cover the delivery area, avoiding fulfillment failures due to mismatched logistics service areas and reducing the risk of abnormal order fulfillment. The activation method of matching rules can be configured through policy-enabled control data, and the range of selectable logistics, alternative warehouse sets, and fallback warehouse sets can be flexibly defined. This adapts to the needs of e-commerce enterprises at different operational stages (such as adding alternative warehouses during promotional periods and limiting high-efficiency logistics during holidays) and for orders from different regions (such as designating dedicated alternative warehouses for specific regions). There is no need to refactor the entire methodology; only rule configuration adjustments are required to quickly respond to changes in the scenario. Furthermore, by setting customer service remarks in the pending order data, the matching logic can be adjusted during the matching process based on special requirements in the remarks (such as specifying logistics type or prioritizing delivery to a specific regional warehouse), further enhancing the adaptability to personalized order needs.

[0058] As an optional implementation, in step S1, warehouse basic data is the core prerequisite for establishing warehouse-based matching logistics, used to clarify the scope and key attributes of warehouses manageable by the system. Warehouse basic data includes: warehouse identification information, warehouse functional attributes, and warehouse basic status. Warehouse identification information includes a unique number for each warehouse (e.g., warehouse 1-warehouse 10), warehouse name (e.g., North China warehouse, East China warehouse), and the region to which the warehouse belongs (e.g., North China, South China, Southwest China, etc., used as the basis for subsequent nearest-location warehouse selection rules). Warehouse functional attributes are used to distinguish between candidate warehouses and backup warehouses. Warehouse basic status indicates whether a warehouse is in an active state (only active warehouses can be included in the matching rules to avoid configuring invalid warehouses).

[0059] As an optional implementation, in step S1, the basic logistics data is the core basis for maintaining logistics tariffs, covering key parameters of logistics services to ensure accurate subsequent tariff calculations. The basic logistics data includes: logistics entity information, logistics billing parameters, and logistics service scope. Logistics entity information includes the logistics company name (e.g., SF Express, JD.com, ZTO Express), logistics type (e.g., standard express, next-day delivery, cold chain), logistics service status (activated / deactivated; only activated logistics can be included in the matching), and effective time (the effective time period of the logistics service to avoid configuring expired logistics). Logistics billing parameters include billing rules (e.g., billing by weight, billing by volume, billing by amount), weight-related parameters (initial weight threshold, initial weight fee, subsequent weight unit, subsequent weight fee, e.g., initial weight 1kg / 12 yuan, subsequent weight 1kg / 8 yuan), and fixed surcharges (e.g., additional service fees for certain warehouses / regions). The logistics service scope refers to the delivery area corresponding to each logistics (e.g., nationwide coverage, limited to North China region, etc., ensuring that the logistics can match the order's delivery address range and avoiding configuring logistics that cannot reach the target area).

[0060] As an optional implementation, in step S1, the warehouse-logistics association data is the key link for matching logistics by warehouse dimension, and it is necessary to clarify the logistics list that each warehouse can connect to. The warehouse-logistics association data includes: the list of available logistics corresponding to each candidate warehouse in the candidate warehouse set (e.g., the North China warehouse can connect to SF Express and JD.com, and the South China warehouse can connect to ZTO Express and YTO Express), and the list of associated logistics corresponding to each backup warehouse in the backup warehouse set (the backup warehouse needs to determine the logistics that can be connected to in advance to ensure that the lowest rate can be selected from the associated logistics of the backup warehouse when the inventory is insufficient).

[0061] As an optional implementation method, in step S1, the cost surcharge data is a necessary supplement to the calculation of the comprehensive fee ("logistics fee + warehouse fixed surcharge"), and the fixed cost parameters of each warehouse need to be determined in advance. The cost surcharge data includes: the fixed cost surcharge amount corresponding to each alternative warehouse and the backup warehouse (e.g., fixed surcharge of 0 yuan for the North China warehouse and fixed surcharge of 1 yuan for the Central China warehouse).

[0062] As an optional implementation, in step S1, the strategy activation control data is the basis for configuring the activation rules of the price-based warehouse and logistics selection strategy, and the activation method and time of the strategy need to be clearly defined. The strategy activation control data includes: strategy activation method (instant activation / timed activation) and optional logistics range limitation data (if it is necessary to limit the optional logistics in the strategy, the limited logistics list needs to be determined in advance; if it is not limited, all logistics will be enabled by default, but the control instruction for whether to limit needs to be clearly defined in advance).

[0063] As an optional implementation, step S2 configures matching rules based on the warehouse and logistics basic data, specifically including the following steps.

[0064] S21: Enable warehouse dimension association mode for logistics matching.

[0065] S22: Based on the warehouse dimension association mode of the logistics matching, according to the warehouse basic data, the logistics basic data and the warehouse-logistics association data, maintain the corresponding logistics cost information according to the warehouse dimension, and automatically establish and identify the warehouse-logistics association relationship.

[0066] S23: Based on the cost surcharge data, the strategy activation control data, and the warehouse-logistics relationship, add a "select warehouse and logistics by tariff" strategy in the order processing flow settings, configure the activation attribute of the "select warehouse and logistics by tariff" strategy, set the fallback warehouse set, the alternative warehouse set, and the fixed cost surcharge parameters for each warehouse, and define the range of selectable logistics. If the range of selectable logistics is not defined, all logistics are included in the selectable range by default.

[0067] As an optional implementation, in step S22, the logistics pricing information includes: pricing identification information, logistics service provider information, logistics service type, service effective status, effective period, billing rules, service coverage area, fixed surcharge amount, initial weight threshold, initial weight fee, subsequent weight unit and subsequent weight fee, etc.

[0068] As an optional implementation, in step S23, the activation attribute includes: immediate activation of the strategy or timed activation. When the strategy is configured to be immediately activated, the strategy of selecting warehouses and logistics by cost takes effect immediately. When the strategy is configured to be timed, a specific activation time node needs to be set.

[0069] As an optional implementation, step S4 matches warehouses and logistics based on the order data to be processed and the matching rules to determine the optimal warehouse-logistics combination, specifically including the following steps.

[0070] S41: Based on the order data to be processed and the matching rules, the inventory validity of each candidate warehouse in the candidate warehouse set is checked in turn, and the target warehouse whose inventory meets the order requirements is selected.

[0071] S42: Calculate the comprehensive cost of logistics associated with each of the target warehouses, and sort the comprehensive costs to obtain a cost ranking result. The comprehensive cost is the sum of the basic logistics cost and the corresponding warehouse fixed cost surcharge.

[0072] S43: Determine the uniqueness of the lowest comprehensive fee based on the fee ranking results. If there are multiple warehouse-logistics combinations with the same lowest comprehensive fee, filter the optimal warehouse-logistics combination based on the geographical distance between the receiving address in the order data to be processed and each of the target warehouses. If the lowest comprehensive fee is unique, directly determine the warehouse-logistics combination corresponding to the lowest comprehensive fee as the optimal warehouse-logistics combination.

[0073] S44: If none of the candidate warehouses in the candidate warehouse set meet the inventory requirements, the backup warehouse in the backup warehouse set will be automatically activated. The inventory of the backup warehouse will not be checked. The logistics with the lowest cost will be selected from the logistics associated with the backup warehouse as the order logistics. If there is no associated logistics, the order logistics information will be left blank to obtain the optimal warehouse-logistics combination.

[0074] As an optional implementation, step S43 involves selecting the optimal warehouse-logistics combination based on the delivery address in the order data to be processed and the geographical distance between each target warehouse, specifically including the following steps.

[0075] S431: Calculate the geographical distance between the receiving address in the order data to be processed and each of the target warehouses to obtain multiple geographical distance values.

[0076] S432: Select the target warehouse corresponding to the smallest geographical distance value among the multiple geographical distance values ​​as the selected warehouse to obtain the optimal warehouse-logistics combination.

[0077] As an optional implementation, after step S44, which selects the logistics with the lowest cost from the backup warehouse-related logistics as the order logistics, the e-commerce order warehouse and logistics matching method further includes the following steps.

[0078] S45: Configure the primary and secondary logistics matching mechanism. This mechanism automatically matches the secondary logistics to the platform to which the order belongs when the selected logistics is the primary logistics provider, ensuring order fulfillment. The primary logistics provider is the manually selected base logistics type when the user maintains the logistics type of a specific logistics company. It serves as the reference for all platform-specific logistics types under that logistics company. For example, when maintaining ZTO Express, the user can select Taobao ZTO as the primary logistics provider. Secondary logistics providers belong to the same logistics company as the primary logistics provider but correspond to platform-specific logistics types on different e-commerce platforms. They supplement and adapt to the primary logistics provider. For example, if Taobao ZTO is the primary logistics provider for ZTO Express, JD ZTO and Douyin ZTO are the corresponding secondary logistics providers.

[0079] As an optional implementation, when determining the uniqueness of the lowest comprehensive tariff in step S43, a tariff difference threshold is preset. When the comprehensive tariff difference of different warehouse-logistics combinations is within the tariff difference threshold, it is determined that the lowest comprehensive tariff of the warehouse-logistics combination is the same; otherwise, it is determined that the lowest comprehensive tariff of the warehouse-logistics combination is different.

[0080] To make the technical solution of this application clearer, the specific implementation process of the technical solution of this application will be explained in detail below with examples. For example... Figure 3 As shown, the specific steps include:

[0081] Step 1: Obtain basic warehouse and logistics data and configure matching rules.

[0082] (1) When logistics matching is enabled by warehouse dimension, the "logistics fees" are maintained according to the warehouse dimension (each warehouse sets its own corresponding logistics fees). This will automatically identify the warehouse-logistics relationship, such as... Figure 4 and Figure 5 As mentioned above, for multi-warehouse users, each warehouse has different logistics. Therefore, the system needs to rely on the warehouse-logistics relationship to determine which warehouse the low-priced logistics belongs to, thus achieving the effect of selecting a warehouse based on pricing.

[0083] (2) Add the "Select Warehouse and Logistics by Rate" strategy in the process settings, and customize the enabled attribute configuration, such as Figure 6 As shown, the system sets up a safety net warehouse, backup warehouses, and corresponding fixed cost surcharges for each warehouse. It clearly defines the sets of safety net and backup warehouses and limits the range of selectable logistics. The lowest cost is calculated from this limited range of selectable logistics; if no selection is made, all logistics are used by default. The fixed cost surcharge for a warehouse refers to costs that do not change with the volume of goods entering or leaving the warehouse, order processing volume, or the quantity of goods stored. These costs include rent, depreciation, labor costs, and other warehouse maintenance costs. Fixed costs can make the additional costs of high-cost warehouses explicit, effectively prioritizing warehouses and guiding warehouse selection.

[0084] Step 2: Obtain the order data to be processed and determine the optimal warehouse-logistics combination.

[0085] After receiving an order, the system collects the order data, including store information, product details, recipient address, and customer service remarks, and then enters the warehouse and logistics matching process. The order data to be processed includes detailed information such as product details, price, shipping and receiving addresses, store information, and customer service remarks from the e-commerce order. The system performs order management operations based on the data provided with the order, including warehouse and logistics selection, order changes, and order approval.

[0086] (1) Inventory verification: Iterate through the candidate warehouses (e.g., warehouse 1 to warehouse 10) and check whether the inventory of each warehouse is sufficient according to the inventory of each warehouse. If the inventory is insufficient, skip the warehouse and continue to check the next warehouse; if the inventory is sufficient, proceed to the logistics cost calculation stage.

[0087] (2) Logistics cost ranking: For warehouses that meet the inventory conditions, calculate the costs of their associated logistics (logistics costs + warehouse fixed surcharges) and rank the calculation results.

[0088] (3) Determine if the rates are consistent: If there are multiple options with the same lowest rate, the nearest warehouse selection rule will be implemented (based on the distance from each warehouse to the delivery address, the warehouse closest to the delivery address will be selected first); if the rate is uniquely the lowest, the warehouse-logistics combination will be selected directly.

[0089] (4) Determine the optimal warehouse-logistics combination: After traversing all warehouse-logistics combinations, select the warehouse-logistics combination with the lowest overall cost as the order's shipping warehouse and logistics, which is the optimal warehouse-logistics combination.

[0090] (5) Backup Mechanism: If all candidate warehouses have no stock, the backup warehouse is automatically selected without checking inventory. The lowest-cost logistics provider associated with the backup warehouse is selected as the order's logistics provider; if no logistics provider is available, the backup warehouse is left blank. By automatically selecting the backup warehouse, the system prevents orders from not being able to select a warehouse. After an order is submitted, a warehouse must be selected before it can proceed to the subsequent review stage. When the system iterates through and checks all the warehouses set in the warehouse and logistics selection strategy and finds that none of them have stock (e.g., none of the 10 warehouses have stock), the order will directly select the set backup warehouse and proceed to the next stage.

[0091] (6) Primary and Secondary Logistics Processing (Optional Configuration): Check "Select corresponding platform logistics through primary logistics", such as Figure 7 As shown, when the primary logistics is selected, the corresponding secondary logistics from the same platform is automatically matched to ensure that the order can be processed and shipped normally.

[0092] In this embodiment, the matching rules for primary and secondary logistics are as follows: major e-commerce platforms sign different electronic waybill agreements with various logistics companies. One logistics company may have multiple logistics types corresponding to different platforms. When maintaining logistics in the user's system, one type is randomly selected as the primary logistics, and the rest are secondary logistics. Logistics between different platforms are not interconnected, and the platform and electronic waybill must be strictly matched; otherwise, it is impossible to print and ship the goods.

[0093] Under the constraints of privacy policies, major e-commerce platforms and logistics companies negotiate to use different electronic waybills, pushing customer privacy information from platform orders to the ERP (Enterprise Resource Planning) system. Therefore, under the same logistics type, there are various secondary logistics types; for example, ZTO Express has Taobao ZTO, JD ZTO, and Douyin ZTO. When users maintain logistics in the system, they randomly select one platform's logistics as the primary logistics, and the others as secondary logistics. For example, a user selects "Taobao ZTO" as the primary logistics type for ZTO Express. However, the electronic waybills of different platforms are not interchangeable. Although they are all ZTO Express, Taobao orders can only use Taobao ZTO. If a Taobao order is matched with JD Logistics, it cannot proceed to the subsequent labeling and shipping stage. The "Primary Logistics and Secondary Logistics Processing" configuration in this application method is designed to solve this problem. When a JD order selects Taobao ZTO under the "select warehouse and logistics by tariff" strategy, the system will find the corresponding logistics type that should be applied to this order based on the primary logistics type maintained in the system, automatically correcting the logistics type to JD ZTO. This configuration ensures the correct correspondence between the platform and the logistics waybill.

[0094] This application automatically selects the optimal warehouse-logistics combination by calculating multi-dimensional data such as inventory status, logistics costs, and delivery distance in real time. This can significantly reduce logistics costs and improve order processing efficiency, providing a smart warehouse and logistics selection decision-making method for the multi-warehouse and multi-logistics operations of medium and large e-commerce companies.

[0095] To verify the advantages of the proposed method over traditional fixed warehouse priority rules in reducing logistics costs and improving decision-making efficiency, a comparative experiment was conducted. Data source: Historical order data from a medium-to-large e-commerce company over the past year, containing 1 million real order records, covering categories such as apparel, digital products, and home furnishings. Warehouse network: Simulated its five core warehouses nationwide (North China, East China, South China, Southwest China, and Central China) and 5-8 mainstream logistics providers (such as SF Express, JD.com, STO Express, YTO Express, ZTO Express, and Yunda Express) connected to each warehouse. Experimental group (proposed method): The proposed algorithm model was applied to calculate inventory, costs, and distance in real time, dynamically selecting the optimal combination. Control group (traditional method): The company's original fixed warehouse priority rules were used (e.g., priority given to East China warehouse -> South China warehouse -> North China warehouse), and the default logistics was selected within the same warehouse. The core indicators of the experiment were average logistics cost per shipment (RMB / shipment), average order processing time (milliseconds), and abnormal order fulfillment rate (%) (indicating whether orders in scenarios such as insufficient inventory can be successfully allocated to a warehousing and distribution plan). The experimental results are shown in Table 1.

[0096] Table 1 Experimental Results

[0097] As can be clearly seen from Table 1, the method described in this application reduces costs by 18.8%. This is because traditional rules mechanically direct orders to high-priority warehouses, even though the logistics costs of those warehouses may not be optimal. In contrast, the method described in this application compares the logistics costs of all available warehouses in real time to find the lowest-cost combination. For example, for an order destined for South China, traditional rules would prioritize allocating it to an East China warehouse (shipping cost 15 yuan), while this method might find that although local shipping from the South China warehouse has a lower priority, the logistics cost is only 10 yuan, thus saving 5 yuan in costs.

[0098] Furthermore, Table 1 clearly shows that this application improves efficiency by 92.2%. This is because, under traditional rules, manually handling abnormal orders (such as out-of-stock items in the preferred warehouse) and manually comparing logistics prices are extremely time-consuming. The method in this application automates the entire process through algorithms, including inventory verification, cost calculation, optimal solution selection, and fallback processing, without human intervention, resulting in extremely fast decision-making speed.

[0099] Furthermore, as can be clearly seen from Table 1, the reliability of the proposed method is improved by 100%. This is because traditional rules can easily lead to order "stuck" when the preferred warehouse is out of stock, requiring manual reassignment of a warehouse, which is inefficient and prone to errors. The proposed method's built-in intelligent backup mechanism automatically switches to a backup warehouse and selects its lowest-cost logistics when any warehouse is out of stock, ensuring that 100% of orders are processed in a timely manner. Through the comparative experiments based on the above real datasets, the effectiveness and feasibility of the proposed method can be clearly verified.

[0100] The experimental data presented above demonstrates that the proposed method significantly outperforms traditional fixed warehouse priority rules in three core dimensions: economy (cost), efficiency (speed), and reliability (backup plan). This not only brings direct economic benefits to enterprises but also greatly improves the automation level and operational efficiency of warehousing and logistics, fully meeting the intelligent management needs of complex multi-warehouse and multi-logistics networks of medium and large e-commerce enterprises.

[0101] Based on the same inventive concept, this application also provides an e-commerce order warehouse and logistics matching processing system for implementing the above-mentioned e-commerce order warehouse and logistics matching method. The solution provided by this e-commerce order warehouse and logistics matching processing system is similar to the solution described in the above method. Therefore, the specific limitations in the following embodiments of the e-commerce order warehouse and logistics matching processing system can be found in the limitations of the e-commerce order warehouse and logistics matching method described above, and will not be repeated here.

[0102] In one exemplary embodiment, such as Figure 8 As shown, an e-commerce order warehouse and logistics matching system is provided, which specifically includes the following modules.

[0103] The basic data acquisition module is used to acquire basic warehouse and logistics data. This basic warehouse and logistics data includes: basic warehouse data, basic logistics data, warehouse-logistics correlation data, cost surcharge data, and policy activation control data.

[0104] The matching rule configuration module is used to configure matching rules based on the warehouse and logistics basic data. The configuration parameters for the matching rules include: selectable logistics range, fallback warehouse set, alternative warehouse set, fixed cost surcharge for each warehouse, and warehouse-logistics association.

[0105] The order data acquisition module is used to acquire order data to be processed. This order data includes: the receiving store, product details, shipping address, and customer service remarks.

[0106] The warehouse-logistics matching module is used to match warehouses and logistics providers based on the order data to be processed and the matching rules, and to determine the optimal warehouse-logistics combination. The optimal warehouse-logistics combination is the one with the lowest overall cost.

[0107] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0108] This document uses specific examples 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 methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for matching warehouses and logistics for e-commerce orders, characterized in that, The method for matching warehouses and logistics for e-commerce orders includes: Acquire basic warehouse and logistics data; the basic warehouse and logistics data includes: basic warehouse data, basic logistics data, warehouse-logistics related data, cost surcharge data, and strategy activation and control data. Based on the aforementioned warehouse and logistics data, matching rules are configured; the configuration parameters of the matching rules include: optional logistics range, backup warehouse set, alternative warehouse set, fixed cost markup for each warehouse, and warehouse-logistics relationship; Acquire pending order data; the pending order data includes: receiving store, product details, shipping address, and customer service remarks; Based on the pending order data and the matching rules, warehouses and logistics are matched to determine the optimal warehouse-logistics combination; the optimal warehouse-logistics combination is the warehouse-logistics combination with the lowest overall cost.

2. The warehouse and logistics matching method for e-commerce orders according to claim 1, characterized in that, The warehouse basic data includes: warehouse identification information, warehouse functional attributes, and warehouse basic status; the logistics basic data includes: logistics entity information, logistics billing parameters, and logistics service scope; the warehouse-logistics association data includes: the optional logistics list corresponding to each optional warehouse in the candidate warehouse set and the associated logistics list corresponding to each backup warehouse in the backup warehouse set; the cost surcharge data includes: the fixed cost surcharge amount corresponding to each of the candidate warehouses and the backup warehouse; the strategy activation control data includes: strategy activation method and optional logistics scope limitation data.

3. The warehouse and logistics matching method for e-commerce orders according to claim 1, characterized in that, Based on the aforementioned warehouse and logistics data, matching rules are configured, specifically including: Enable warehouse-level association mode for logistics matching; Based on the warehouse dimension association mode of the logistics matching, according to the warehouse basic data, the logistics basic data and the warehouse-logistics association data, the corresponding logistics cost information is maintained according to the warehouse dimension, and the warehouse-logistics association relationship is automatically established and identified. Based on the cost surcharge data, the strategy activation control data, and the warehouse-logistics relationship, a "select warehouse and logistics by tariff" strategy is added to the order processing flow settings. The activation attribute of the "select warehouse and logistics by tariff" strategy is configured, a fallback warehouse set, a backup warehouse set, and fixed cost surcharge parameters for each warehouse are set, and the range of selectable logistics is defined. If the range of selectable logistics is not defined, all logistics are included in the selectable range by default.

4. The warehouse and logistics matching method for e-commerce orders according to claim 3, characterized in that, The logistics pricing information includes: pricing identification information, logistics service provider information, logistics service type, service activation status, activation period, billing rules, service coverage area, fixed surcharge amount, initial weight threshold, initial weight fee, subsequent weight unit and subsequent weight fee.

5. The warehouse and logistics matching method for e-commerce orders according to claim 3, characterized in that, The activation attributes include: immediate activation or scheduled activation. When configuring scheduled activation, a specific activation time node needs to be set.

6. The warehouse and logistics matching method for e-commerce orders according to claim 1, characterized in that, Based on the pending order data and the matching rules, warehouses and logistics are matched to determine the optimal warehouse-logistics combination, specifically including: Based on the order data to be processed and the matching rules, the inventory validity of each candidate warehouse in the candidate warehouse set is checked in turn to filter out the target warehouse whose inventory meets the order requirements. Calculate the comprehensive cost of logistics associated with each of the target warehouses, and sort the comprehensive costs to obtain the cost ranking result; the comprehensive cost is the sum of the basic logistics cost and the corresponding warehouse fixed cost surcharge parameter; The uniqueness of the lowest comprehensive fee is determined based on the fee ranking results. If there are multiple warehouse-logistics combinations with the same lowest comprehensive fee, the optimal warehouse-logistics combination is selected based on the geographical distance between the receiving address in the order data to be processed and each of the target warehouses. If the lowest comprehensive fee is unique, the warehouse-logistics combination corresponding to the lowest comprehensive fee is directly determined as the optimal warehouse-logistics combination. If none of the candidate warehouses in the candidate warehouse set meet the inventory requirements, the fallback warehouse in the fallback warehouse set will be automatically activated. The inventory of the fallback warehouse will not be checked. The logistics with the lowest cost will be selected from the logistics associated with the fallback warehouse as the order logistics. If there is no associated logistics, the order logistics information will be left blank to obtain the optimal warehouse-logistics combination.

7. The warehouse and logistics matching method for e-commerce orders according to claim 6, characterized in that, The optimal warehouse-logistics combination is selected based on the delivery address in the pending order data and the geographical distance to each target warehouse, specifically including: Calculate the geographical distance between the receiving address in the order data to be processed and each of the target warehouses to obtain multiple geographical distance values; The target warehouse corresponding to the smallest geographical distance value among the multiple geographical distance values ​​is selected as the warehouse to obtain the optimal warehouse-logistics combination.

8. The warehouse and logistics matching method for e-commerce orders according to claim 6, characterized in that, After the step of selecting the logistics with the lowest cost from the associated logistics of the backup warehouse as the order logistics, the warehouse and logistics matching method for e-commerce orders further includes: Configure a primary and secondary logistics matching mechanism; the primary and secondary logistics matching mechanism means that when the selected logistics is the primary logistics, the secondary logistics corresponding to the platform to which the order belongs is automatically matched to ensure the normal fulfillment of the order; the primary logistics is the logistics of the baseline logistics type manually selected by the user when maintaining the logistics type of a certain logistics company; the secondary logistics is the logistics of the platform-specific logistics type that belongs to the same logistics company as the primary logistics but corresponds to a different e-commerce platform.

9. The warehouse and logistics matching method for e-commerce orders according to claim 6, characterized in that, When determining the uniqueness of the lowest comprehensive tariff, a tariff difference threshold is preset. When the comprehensive tariff difference of different warehouse-logistics combinations is within the tariff difference threshold, it is determined that the lowest comprehensive tariff of the warehouse-logistics combination is the same.

10. A warehouse and logistics matching system for e-commerce orders, characterized in that, The e-commerce order warehouse and logistics matching system is used to implement the e-commerce order warehouse and logistics matching method according to any one of claims 1-9, wherein the e-commerce order warehouse and logistics matching system includes: The basic data acquisition module is used to acquire warehouse and logistics basic data; the warehouse and logistics basic data includes: warehouse basic data, logistics basic data, warehouse-logistics related data, cost surcharge data, and strategy activation control data. The matching rule configuration module is used to configure matching rules based on the warehouse and logistics basic data; the configuration parameters of the matching rules include: optional logistics range, backup warehouse set, alternative warehouse set, fixed cost surcharge for each warehouse, and warehouse-logistics association relationship; The order data acquisition module is used to acquire order data to be processed; the order data to be processed includes: receiving store, product details, delivery address and customer service remarks; The warehouse-logistics matching module is used to match warehouses and logistics based on the order data to be processed and the matching rules, and to determine the optimal warehouse-logistics combination; the optimal warehouse-logistics combination is the warehouse-logistics combination with the lowest overall cost.

Images