A multi-node inventory sharing and intelligent allocation system and method

Abstract

The present application belongs to the technical field of marketing inventory management, and discloses a multi-network point inventory sharing and intelligent allocation system and method. The method collects sales flow and commodity time limit of each sales network point, determines the inventory digestion period based on sales data, classifies the network points in combination with the replenishment period and the reasonable turnover period of commodities, accurately divides the short-supply network points and the slow-selling network points, selects the network points with surplus short-supply commodities from the slow-selling network points to form a candidate allocation set, comprehensively calculates the transportation cost between network points, the loss value of sales opportunity of the slow-selling network points, and the allowance amount of near-expiration commodities, obtains the comprehensive cost of each candidate network point by fusing multiple costs, generates an allocation suggestion instruction by selection, dynamically adjusts the allocation scheme in combination with the negotiation feedback of the supply and demand sides, and solves the industry pain points such as single cost accounting, rough supply and demand determination, and low allocation communication efficiency of traditional network point inventory allocation, so as to realize multi-network point inventory sharing and intelligent and low-cost efficient allocation.

Description

Technical Field

[0001] This invention relates to the field of marketing inventory management technology, and in particular to a multi-site inventory sharing and intelligent allocation system and method. Background Technology

[0002] With the rapid development of multi-store chain operation models, inventory sharing and cross-store transfer management have become core research topics in the field of supply chain digitalization. Currently, most of these models focus on centralized inventory data statistics, collecting real-time inventory data from various sales outlets to directly determine out-of-stock and slow-moving outlets based on inventory balances. Transfer instructions are then formulated based on a unified management model from headquarters. These technologies provide technical support for basic inventory management in multi-store enterprises and have been applied on a large scale in industries such as FMCG and physical retail.

[0003] However, existing technologies only calculate basic transportation costs without incorporating key cost factors such as lost sales opportunities at the outlets and discounts on near-expiry goods. This makes it impossible to form a scientific and comprehensive scheduling cost assessment system, which makes it difficult to select the optimal allocation plan. Consequently, allocation pricing lacks a basis, and the distribution of benefits among outlets becomes unreasonable. This leads to a chain of problems such as store resistance to allocation, difficulty in digesting near-expiry inventory, and low efficiency of centralized scheduling. It fails to meet the actual needs of efficient sharing and intelligent collaborative allocation of inventory across multiple outlets. Summary of the Invention

[0004] This invention provides a multi-site inventory sharing and intelligent allocation system and method, the main purpose of which is to solve the problems of one-sided cost calculation, crude judgment of supply and demand of outlets, inefficient allocation negotiation, and difficulty in revitalizing near-expiry inventory in the existing multi-site inventory allocation system.

[0005] To achieve the above objectives, the present invention provides a multi-site inventory sharing and intelligent allocation system, comprising: Data acquisition module: Collects sales records and expiration dates of goods sold at each sales outlet; Classification and labeling module: Based on the sales transaction records of the sales outlets, determine the inventory digestion cycle of the sold goods, compare the replenishment cycle of the time limit and the reasonable turnover cycle of the goods with the inventory digestion cycle respectively, and mark the sales outlets as out-of-stock outlets and slow-moving outlets according to the comparison results respectively; Product screening module: Screens out outlets that hold out-of-stock products and whose inventory is higher than their own safety stock from the slow-moving outlets, forming a candidate transfer set; Cost calculation module: Analyzes the transportation costs between the candidate centralized outlets and the out-of-stock outlets, calculates the sales opportunity loss value of the slow-moving outlets during the replenishment cycle, and generates a discount amount based on the shelf life of the out-of-stock goods; Cost fusion module: It integrates the transportation cost, the lost sales opportunity value and the discount amount to obtain the comprehensive scheduling cost of each network point in the candidate transfer set, and selects the candidate scheme with the minimum comprehensive scheduling cost to generate a suggested transfer instruction; Intelligent allocation module: The suggested allocation instruction is sent to the corresponding out-of-stock outlets and slow-moving outlets. Based on the feedback and negotiation requests from the out-of-stock outlets and slow-moving outlets, the suggested allocation instruction is adjusted and sent again until both parties confirm and the allocation is executed.

[0006] Preferably, determining the inventory clearance cycle of the sold goods based on the sales records of the sales outlets includes: Extract the sales volume of the sold goods per unit time from the sales transaction record, and query the current inventory of the corresponding sold goods from the real-time inventory system of the sales outlet. Combine the sales volume per unit time with the current inventory to determine the inventory digestion cycle of the sold goods.

[0007] Preferably, the step of comparing the replenishment cycle and reasonable inventory turnover cycle of the time limit with the inventory digestion cycle, and marking the sales outlets as out-of-stock outlets and slow-moving outlets based on the comparison results, includes: Extract the replenishment cycle and reasonable inventory turnover cycle of the sold goods from the aforementioned time limit; Compare the replenishment cycle with the inventory clearance cycle, analyze the stockout risk value of the sold goods, and determine the stockout locations of the sales outlets based on the stockout risk value; By comparing the reasonable turnover cycle of the goods with the inventory digestion cycle, the unsold risk value of the goods is analyzed, and the unsold risk value is used to determine whether the sales outlet is an unsold outlet.

[0008] Preferably, the step of selecting outlets from the slow-moving outlets that hold out-of-stock goods and whose inventory levels exceed their own safety stock, forming a candidate transfer set, includes: Based on the list of out-of-stock items at the out-of-stock outlets, filter all the inventory data of the slow-moving outlets, and match the list of out-of-stock items with the inventory data one by one, and filter out the matching outlets that match the out-of-stock outlets from the slow-moving outlets; Obtain the safety stock threshold and inventory quantity of the out-of-stock items in the list of out-of-stock items from the matching outlets, compare the safety stock threshold and the inventory quantity, retain outlets where the safety stock threshold is greater than the inventory quantity, and package them into a candidate recall set.

[0009] Preferably, the analysis of transportation costs between the candidate centralized distribution points and the out-of-stock distribution points includes: Extract the transportation routes between each outlet in the candidate dispatch set and the outlets experiencing stock shortages, and generate candidate transportation routes based on the actual traffic conditions of the transportation routes; Based on the physical properties and shelf life of the out-of-stock goods, select a suitable means of transportation for the out-of-stock goods, and select the optimal route from the candidate transportation routes by combining real-time traffic data and historical transportation efficiency records. The transportation cost generated by temporary scheduling is obtained by integrating the travel time cost, transportation vehicle adaptation cost, and route usage cost of the optimal route.

[0010] Preferably, calculating the lost sales opportunity value of the slow-moving outlets during the replenishment cycle includes: Based on the historical sales records of the slow-moving outlets, the daily average sales and actual sales volatility of the out-of-stock products are extracted to predict the expected sales trend of the out-of-stock products during the replenishment cycle. Analyze the inventory turnover rate of the substitute products for the out-of-stock items during the replenishment cycle, analyze the potential loss opportunities of the out-of-stock items, and combine the potential loss opportunities with the expected sales trend to obtain the sales opportunity loss value caused by temporary scheduling.

[0011] Preferably, the step of generating a discount amount based on the shelf life of the out-of-stock goods includes: The shelf life of the out-of-stock products is divided according to the length of time, and a discount coefficient is assigned to each interval. The historical sales speed and inventory digestion cycle of the out-of-stock products are analyzed to generate the slow-moving factor of the out-of-stock products. By combining the slow-moving factor and the discount coefficient, and associating them with the initial cost of the out-of-stock goods, a discount amount for the out-of-stock goods is generated.

[0012] Preferably, the process of integrating the transportation cost, the lost sales opportunity value, and the discount amount to obtain the comprehensive scheduling cost of each network point in the candidate transfer-out group, and selecting the candidate scheme with the minimum comprehensive scheduling cost to generate a suggested transfer instruction, includes: The transportation cost, the lost sales opportunity value, and the discount amount are normalized, and dynamic weights are assigned to the normalized transportation cost, the lost sales opportunity value, and the discount amount. The transportation cost after dynamic weight allocation, the lost sales opportunity value, and the discount amount are integrated, and the overall scheduling cost of each point in the candidate transfer set is calculated by weighted summation. Compare the overall scheduling costs of all outlets in the candidate transfer set, select the slow-moving outlet with the lowest cost as the transferor, and generate a suggested transfer instruction.

[0013] Preferably, the step of adjusting the suggested transfer instruction and re-delivering it based on the feedback and negotiation requests from the out-of-stock outlets and the slow-moving outlets, until both parties confirm and the transfer is executed, includes: After the suggested allocation instruction is issued, the system collects the stock-out outlets' requests for adjustments to replenishment timeliness and their opinions on cost allocation from the slow-moving outlets, and packages them into a two-way feedback negotiation request data packet. Based on the conflict indicators in the feedback negotiation request data packet, the suggested allocation instruction is dynamically adjusted to generate the final allocation instruction confirmed by both parties.

[0014] To address the aforementioned problems, this invention also provides a method for multi-site inventory sharing and intelligent allocation, comprising: Collect sales records and product expiration dates for each sales outlet; Based on the sales records of the sales outlets, the inventory digestion cycle of the sold goods is determined. The replenishment cycle and reasonable turnover cycle of the goods with the expiration date are compared with the inventory digestion cycle, and the sales outlets are marked as out-of-stock outlets and slow-moving outlets based on the comparison results. From the aforementioned slow-moving outlets, outlets holding out-of-stock goods and whose inventory levels exceed their own safety stock are selected to form a candidate transfer set; Analyze the transportation costs between the candidate centralized outlets and the out-of-stock outlets, calculate the sales opportunity loss value of the slow-moving outlets during the replenishment cycle, and generate a discount amount based on the shelf life of the out-of-stock goods. By integrating the transportation cost, the lost sales opportunity value, and the discount amount, the overall scheduling cost of each network point in the candidate transfer-out group is obtained, and the candidate scheme with the minimum overall scheduling cost is selected to generate a suggested transfer instruction; The suggested transfer order is sent to the corresponding out-of-stock outlets and slow-moving outlets. Based on the feedback and negotiation requests from the out-of-stock outlets and slow-moving outlets, the suggested transfer order is adjusted and sent again until both parties confirm and the transfer is executed.

[0015] Beneficial effects This solution uses data on sales volume and product expiration dates from various outlets to calculate the inventory digestion cycle, enabling precise classification and labeling of outlets with stockouts and slow-moving inventory. It achieves accurate identification and matching of supply and demand for inventory across multiple outlets, solving the problems of crude supply and demand judgments at outlets and simple division of supply and demand based solely on inventory balances in existing technologies. This solution offers the advantage of efficient utilization of inventory resources.

[0016] This solution selects outlets with out-of-stock items and inventory levels exceeding their own safety stock to form a candidate transfer pool. This allows for the discovery of surplus inventory while ensuring the normal operation of the outlets, enabling the cross-outlet transfer of slow-moving and near-expiry goods. It solves the problems of store inventory backlog, difficulty in selling near-expiry goods, and idle and wasted inventory resources in the traditional model, and has the advantages of reducing store inventory losses and improving overall inventory turnover efficiency.

[0017] This solution achieves comprehensive and accurate accounting of overall allocation costs by integrating three core data points: transportation costs, lost sales opportunities at slow-moving outlets, and discounts on near-expiry goods. It intelligently generates the allocation plan with the lowest overall cost, solving the problems of single cost accounting, lack of basis for allocation pricing, and unreasonable distribution of benefits among outlets in existing technologies. It has the core benefits of balancing the interests of both supply and demand sides and reducing overall allocation costs. Attached Figure Description

[0018] Figure 1 This is a functional module diagram of a multi-site inventory sharing and intelligent allocation system provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating a method for sharing and intelligently allocating inventory across multiple locations, as provided in an embodiment of the present invention. The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides a multi-site inventory sharing and intelligent allocation system and method. The executing entity of the multi-site inventory sharing and intelligent allocation system and method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the multi-site inventory sharing and intelligent allocation system and method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0021] Reference Figure 1The diagram shown is a functional block diagram of a multi-site inventory sharing and intelligent allocation system provided in an embodiment of the present invention.

[0022] The multi-site inventory sharing and intelligent allocation system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the multi-site inventory sharing and intelligent allocation system 100 may include a data acquisition module 101, a classification and marking module 102, a product screening module 103, a cost calculation module 104, a cost fusion module 105, and an intelligent allocation module 106. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0023] In this embodiment, the functions of each module / unit are as follows: Data acquisition module 101: Collects sales records and expiration dates of goods sold at each sales outlet; Specifically, sales outlets refer to offline physical stores or online sales sites under the brand's operating entity that have independent authority to sell goods and manage inventory. They are the smallest business unit collected and correspond to offline business locations with actual business operations, such as chain supermarkets, brand-operated / franchised stores, and regional retail sites.

[0024] Sales transaction records refer to the full-volume structured transaction details generated by all sales activities of each sales outlet within a predetermined operating cycle. They are the core basic parameters for calculating the sales volume per unit time, inventory digestion cycle, and sales trends of goods, and are obtained through the POS sales system and online transaction system of the sales outlets.

[0025] Goods for sale refer to standardized, salable goods that are included in the sales outlet's inventory management system, have external sales qualifications, clear pricing, and complete timeliness information. They are the core target of inventory management and allocation operations.

[0026] The expiration date refers to a set of time attribute parameters that are strongly tied to the products being sold and cover the entire life cycle of the products. It is the core data source for subsequent replenishment cycles, reasonable product turnover cycles, shelf life, and near-expiration discount calculations. It is obtained through the product master data management system and includes time-related parameters such as product shelf life, fixed replenishment cycles stipulated by the brand, reasonable product turnover cycles commonly used in the industry, and near-expiration product classification warning thresholds.

[0027] Furthermore, firstly, the system integrates with the sales management system, inventory management system, and product file system of each sales outlet. Following a pre-set fixed collection frequency, it acquires all sales transaction records for each independent sales outlet within its corresponding operating cycle. Simultaneously, it captures all pre-set expiration date parameters for the corresponding products in the main product database. The system then performs cleaning operations on the collected raw data, including deduplication, outlier filtering, data format standardization, and missing field completion. Finally, the processed compliant structured data is synchronously pushed to the next-level classification and labeling module of the system, providing complete, accurate, and unified data source support for subsequent outlet supply and demand attribute determination and inventory allocation plan generation.

[0028] For example, a chain convenience store brand has 35 directly operated sales outlets in a certain area, mainly selling standardized retail goods such as pre-packaged food, low-temperature dairy products, and daily necessities. This solution connects with the POS sales management system, inventory management system, and product file system of the 35 outlets through an encrypted API interface. It is set to collect all the previous day's operating data at 2:00 AM every day, and also supports the incremental collection of real-time transaction data once per hour.

[0029] During the actual data collection process, the complete sales records of 35 outlets from the previous day were retrieved, including core fields such as the unique product code, sales time, sales quantity, and affiliated store for each transaction. Simultaneously, the expiration date parameters for all sold products were retrieved, including the shelf life of each product, the weekly replenishment cycle stipulated by headquarters, the reasonable turnover cycle for products commonly used in the FMCG industry, and the grading and early warning threshold for near-expiration products. After data cleaning and standardization, the compliant structured data was synchronously pushed to the classification and labeling module for subsequent calculation of inventory digestion cycles at each outlet, and for classifying and labeling outlets with stockouts and slow-moving inventory. This provides basic data support for the entire process of subsequent cross-outlet inventory transfers.

[0030] Classification and labeling module 102: Based on the sales transaction records of the sales outlets, determine the inventory digestion cycle of the sold goods, compare the replenishment cycle of the time limit and the reasonable turnover cycle of the goods with the inventory digestion cycle respectively, and label the sales outlets as out-of-stock outlets and slow-moving outlets according to the comparison results respectively; In this embodiment, determining the inventory clearance cycle of the sold goods based on the sales transaction records of the sales outlets includes: Extract the sales volume of the sold goods per unit time from the sales transaction record, and query the current inventory of the corresponding sold goods from the real-time inventory system of the sales outlet. Combine the sales volume per unit time with the current inventory to determine the inventory digestion cycle of the sold goods.

[0031] Specifically, sales volume per unit time refers to the average number of goods sold within a fixed statistical period, extracted from sales records. It is a core indicator reflecting the sales rate of goods and calculating the duration that inventory can support sales. The statistical period can be set to daily, weekly, monthly, or other dimensions according to the characteristics of the product category.

[0032] A real-time inventory system refers to a digital management system deployed at various sales outlets and brand headquarters to record, update, and query the remaining inventory and inventory change details of all products in real time. It can also provide synchronous feedback on the real-time inventory status of the corresponding products at the corresponding outlets.

[0033] Current inventory refers to the actual remaining quantity of the corresponding sales product at the query node, obtained from the real-time inventory system of the sales outlet. It is the core basis for calculating the inventory digestion cycle and only includes compliant inventory that can be sold normally, excluding defective, near-expiry, and unsellable inventory such as sold but not picked up.

[0034] Inventory digestion cycle refers to the length of time that the current inventory can support the normal sales of a product, calculated by combining the sales volume of the product per unit time with the current inventory level. It is the core basis for subsequent determination of the out-of-stock / slow-moving attributes of outlets and the formulation of allocation strategies.

[0035] Furthermore, firstly, from the sales transaction records of each sales outlet that have been collected and cleaned, the sales details of the corresponding products within a fixed statistical period are extracted, the sales volume of the product per unit time is calculated, and a targeted inventory query request is simultaneously initiated to the real-time inventory system of the corresponding sales outlet to retrieve and verify the current inventory of the product at the corresponding outlet.

[0036] Based on the calculated sales volume per unit time, and combined with the extracted current inventory, the calculation of the sales duration that the inventory can support is completed, and the inventory digestion cycle of the sold product at the corresponding sales outlet is confirmed, providing core data support for subsequent outlet classification and labeling, and supply and demand attribute determination.

[0037] For example, for bottled drinking water at outlet A, the system first extracts the full sales details of the product from the sales records of the past 7 days collected from the outlet, calculating that the sales volume per unit time is 40 bottles per day. Simultaneously, it connects to the real-time inventory system of outlet A to query and obtain the current inventory of the product, which is 200 bottles, completing the compliance verification of the inventory base. Finally, the system combines the sales volume per unit time of the product with the current inventory to calculate and confirm that the inventory digestion cycle of the product at outlet A is 5 days, completing the calculation operation of the inventory digestion cycle of the product. This data will be simultaneously pushed to the classification and labeling module for subsequent determination of the outlet's out-of-stock and slow-moving attributes.

[0038] In this embodiment, the step of comparing the replenishment cycle and reasonable inventory turnover cycle of the time limit with the inventory digestion cycle, and marking the sales outlets as out-of-stock outlets and slow-moving outlets based on the comparison results, includes: Extract the replenishment cycle and reasonable inventory turnover cycle of the sold goods from the aforementioned time limit; Compare the replenishment cycle with the inventory clearance cycle, analyze the stockout risk value of the sold goods, and determine the stockout locations of the sales outlets based on the stockout risk value; By comparing the reasonable turnover cycle of the goods with the inventory digestion cycle, the unsold risk value of the goods is analyzed, and the unsold risk value is used to determine whether the sales outlet is an unsold outlet.

[0039] Specifically, the replenishment cycle is a fixed replenishment interval extracted from the expiration date and preset by the brand for the products sold. It is a fixed cycle for the brand headquarters to replenish regular products to various sales outlets. It is the core benchmark parameter for judging the risk of stockouts at outlets and is uniformly set by the brand's supply chain management department and synchronized to the product master data system.

[0040] The reasonable inventory turnover cycle is extracted from the expiration date, is the standard turnover time for goods from warehousing to completion of sales that is common in the corresponding industry, and is an industry benchmark value for measuring whether the inventory turnover efficiency of goods is healthy. It is a core benchmark parameter for judging the risk of unsold goods at the outlet, and is determined based on the common standards of the retail industry and the brand's own operating characteristics.

[0041] The stockout risk value is generated by comparing and analyzing the replenishment cycle and the inventory digestion cycle. It is a numerical indicator that quantifies the possibility of stockouts of the corresponding products at the sales outlet within the normal replenishment cycle. The higher the value, the higher the risk of stockouts.

[0042] The risk value for slow-moving inventory is generated by comparing and analyzing the reasonable turnover cycle of goods with the inventory digestion cycle. It is a quantitative indicator that represents the possibility of inventory backlog and slow-moving inventory at a sales outlet when the inventory turnover efficiency of the corresponding goods is lower than the industry's healthy standard. The higher the value, the higher the risk of slow-moving inventory and backlog.

[0043] Out-of-stock outlets, determined by their out-of-stock risk value, are sales outlets with a higher risk of stockouts because their inventory turnover cycle is shorter than their replenishment cycle. These outlets are the demand side for goods in inventory transfer operations.

[0044] Based on the assessment of slow-moving inventory risk, sales outlets that correspond to a longer inventory digestion cycle than the reasonable turnover cycle of goods and have a higher risk of inventory backlog are potential suppliers of goods in inventory transfer operations.

[0045] Furthermore, firstly, two benchmark parameters, namely the replenishment cycle and the reasonable turnover cycle of the corresponding sales products, are extracted. Then, the extracted replenishment cycle is compared with the inventory digestion cycle of the corresponding outlet for that product. Based on the difference between the two cycles and a preset threshold, the stockout risk value of the product is calculated. Finally, according to the classification and judgment rules of the stockout risk value, the stockout attribute of the corresponding sales outlet is marked, and the stockout outlet is locked.

[0046] Simultaneously, the extracted reasonable turnover cycle of goods is compared with the inventory digestion cycle of the corresponding outlet. Based on the difference between the two cycles and a preset threshold, the unsaleable risk value of the goods is calculated. Then, according to the classification and judgment rules of the unsaleable risk value, the unsaleable attribute of the corresponding sales outlet is marked, the unsaleable outlet is identified and locked, and finally the supply and demand two-way classification and marking of all sales outlets is completed, providing accurate supply and demand subject basis for subsequent candidate transfer set screening and transfer plan generation.

[0047] The rule for classifying stockout risk is that when the inventory digestion cycle is shorter than the replenishment cycle, the difference between the two is positive, and the larger the difference, the higher the stockout risk. That is, the number of days that the existing inventory can be sold is shorter than the number of days that the next batch of replenishment will arrive. The larger the difference, the longer the stockout gap, and the higher the stockout risk level. The corresponding outlet will be marked as a stockout outlet.

[0048] The grading rule for the risk of slow-moving inventory is that when the inventory digestion cycle is longer than the reasonable turnover cycle of the goods, the difference between the two is positive, and the larger the difference, the higher the risk of slow-moving inventory. That is, if the number of days that the goods are actually sold out exceeds the healthy turnover days set by the industry and brand, the larger the difference, the more serious the inventory backlog, the higher the level of slow-moving inventory risk, and the corresponding outlet will be marked as a slow-moving outlet.

[0049] For example, the pre-set replenishment cycle for room-temperature yogurt at outlet A is 7 days, and the reasonable turnover cycle for this type of pre-packaged dairy product in the fast-moving consumer goods (FMCG) retail industry is 15 days. These parameters have been entered into the expiration date module of the product master data system. By collecting sales and inventory data from 35 outlets, the inventory digestion cycle for room-temperature yogurt at outlet A is calculated to be 5 days, and at outlet B, it is 22 days.

[0050] First, the replenishment cycle of 7 days is compared with the inventory digestion cycle of 5 days at point A. The calculated risk value of the out-of-stock risk for this product at point A has reached the risk threshold, and point A is determined to be an out-of-stock point. At the same time, the reasonable product turnover cycle of 15 days is compared with the inventory digestion cycle of 22 days at point B. The calculated risk value of the slow-moving risk for this product at point B has reached the risk threshold, and point B is determined to be a slow-moving point. In this way, the out-of-stock and slow-moving attributes of all 35 points are classified and marked.

[0051] Product screening module 103: Screens out outlets that hold out-of-stock products and whose inventory is higher than their own safety stock from the slow-moving outlets, forming a candidate transfer set; In this embodiment, the step of selecting outlets from the slow-moving outlets that hold out-of-stock goods and whose inventory is higher than their own safety stock to form a candidate transfer set includes: Based on the list of out-of-stock items at the out-of-stock outlets, filter all the inventory data of the slow-moving outlets, and match the list of out-of-stock items with the inventory data one by one, and filter out the matching outlets that match the out-of-stock outlets from the slow-moving outlets; Obtain the safety stock threshold and inventory quantity of the out-of-stock items in the list of out-of-stock items from the matching outlets, compare the safety stock threshold and the inventory quantity, retain outlets where the safety stock threshold is greater than the inventory quantity, and package them into a candidate recall set.

[0052] Specifically, the out-of-stock list is generated based on the sales flow, inventory digestion cycle and replenishment cycle of the out-of-stock outlets. It is a detailed list of products that are at risk of being out of stock and cannot meet the sales demand within the regular replenishment cycle. The core information includes standardized information such as the product's unique code, product name, quantity of out-of-stock shortage, and demand timeliness. It is the core benchmark for screening potential outlets to be transferred out.

[0053] The inventory data is obtained from the real-time inventory system of slow-moving outlets. It is a detailed list of real-time available inventory for the corresponding products. The core data includes fields such as the product's unique code, current available inventory, product shelf life, and warehousing time. Only compliant inventory that can be sold normally is counted, and unsellable inventory such as defective products, near-expiry locked products, and sold but not picked up is excluded.

[0054] Matching outlets are selected from all unsold outlets by matching the list of out-of-stock items with the inventory data one by one. The outlets whose inventory contains the corresponding items in the list of out-of-stock items are the potential suppliers that are initially eligible to be transferred.

[0055] Safety stock threshold, also known as self-safety stock, is the minimum inventory level that a single product must retain to ensure normal sales demand at sales outlets during the replenishment cycle. It is calculated by combining the product's sales volume per unit time, replenishment cycle, and historical sales volatility. It is a core benchmark parameter for determining whether an outlet has surplus inventory that can be transferred out. It is preset and generated based on the product's historical sales data, replenishment cycle, and the outlet's operating characteristics.

[0056] Inventory quantity specifically refers to the current available inventory quantity of the products corresponding to the out-of-stock list within the matched outlets. It is obtained by the system through a targeted query from the real-time inventory system of the matched outlets and only includes compliant inventory that can be sold normally. It is the core comparison value for safety stock verification.

[0057] The candidate transfer set is a set of slow-moving outlets that have out-of-stock products and whose inventory exceeds their own safety stock threshold after being screened for product matching and safety stock threshold verification. It is the core scope for subsequent transfer cost accounting and selection of the optimal transferor.

[0058] Furthermore, firstly, a standardized list of out-of-stock items is extracted and generated. Using this list as the core screening criterion, the real-time inventory data of all marked slow-moving outlets is fully traversed. The product information in the out-of-stock items list is matched and verified with the inventory data of each slow-moving outlet on a product-by-product basis. The slow-moving outlets with corresponding out-of-stock items in their inventory are then selected to form a set of matching outlets.

[0059] Subsequently, the preset safety stock threshold and real-time available inventory of out-of-stock products for all outlets in the matching outlet set are retrieved. The two values ​​are compared and verified on an outlet-by-outlet and product-by-product basis. Only outlets with inventory levels higher than their own safety stock thresholds and with surplus inventory available for transfer are retained. Finally, outlets that meet all the screening criteria are packaged and integrated to form a candidate transfer set that is eligible for compliant transfer.

[0060] For example, regarding outlet A, it has been determined that outlet A is out of stock of ambient temperature yogurt, while outlets B, C, D, and E are outlets with slow-moving ambient temperature yogurt. First, the out-of-stock list of outlet A is extracted. This list includes the unique code of the ambient temperature yogurt, the quantity of 120 boxes out of stock, and the core information on demand within 3 days. Based on this list, the system traverses the real-time inventory data of the four slow-moving outlets, matching the out-of-stock items with the inventory data one by one, and filtering out outlets B, C, and D that have the ambient temperature yogurt in their inventory, forming a matching outlet set.

[0061] The system then retrieved the preset safety stock thresholds and real-time available inventory of the room-temperature yogurt from three outlets: B, C, and D. Outlet B had a safety stock threshold of 30 boxes and a real-time available inventory of 85 boxes; outlet C had a safety stock threshold of 25 boxes and a real-time available inventory of 60 boxes; and outlet D had a safety stock threshold of 20 boxes and a real-time available inventory of 18 boxes. After comparing and verifying the two values, outlet D, whose inventory was below the safety stock threshold, was removed, while outlets B and C, which met the surplus inventory requirements, were retained. Finally, outlets B and C were packaged and integrated to form the candidate set for the transfer of room-temperature yogurt products in this transaction.

[0062] Cost calculation module 104: Analyzes the transportation costs between the candidate centralized outlets and the out-of-stock outlets, calculates the sales opportunity loss value of the slow-moving outlets during the replenishment cycle, and generates a discount amount based on the shelf life of the out-of-stock goods; In this embodiment, analyzing the transportation costs between the candidate centralized distribution points and the out-of-stock distribution points includes: Extract the transportation routes between each outlet in the candidate dispatch set and the outlets experiencing stock shortages, and generate candidate transportation routes based on the actual traffic conditions of the transportation routes; Based on the physical properties and shelf life of the out-of-stock goods, select a suitable means of transportation for the out-of-stock goods, and select the optimal route from the candidate transportation routes by combining real-time traffic data and historical transportation efficiency records. The transportation cost generated by temporary scheduling is obtained by integrating the travel time cost, transportation vehicle adaptation cost, and route usage cost of the optimal route.

[0063] Specifically, a transport route is a set of physical road routes that meet the conditions for freight transport between candidate dispatch points and out-of-stock points. It includes all basic road routes that can be used for freight transport between points within the city, including urban arterial roads, secondary arterial roads, and branch roads that have the qualifications for freight transport.

[0064] Actual traffic conditions are a set of real-time and fixed traffic attribute parameters of the physical roads corresponding to the transportation route, including physical and management constraints that affect the passage of goods transportation, such as road traffic restriction rules, road width, truck passage permissions, road construction status, number of traffic lights, and number of lanes.

[0065] Candidate transportation routes are generated based on transportation routes between outgoing and out-of-stock outlets, combined with actual traffic conditions. They are a complete set of traffic schemes that can realize the transportation of goods between two points. Each route is an executable transportation route with a complete starting point, passing nodes, and destination. Each route corresponds to a unique route combination and traffic rules.

[0066] Real-time traffic data refers to the real-time traffic status data of the roads along the corresponding transportation routes. It includes dynamically updated road traffic data such as real-time traffic flow, average vehicle speed, congestion level, temporary traffic control information, and temporary road construction information. It is obtained through real-time data collection from third-party traffic data platforms or our own transportation fleet.

[0067] Historical transportation efficiency records are stored in the system. They correspond to the historical transportation performance data of candidate transportation routes within the same time period and cycle, such as transportation duration, on-time rate, and probability of congestion. These are structured data accumulated from past allocation and transportation behaviors and are used to predict the transportation efficiency of routes.

[0068] The optimal route is selected from candidate transportation routes based on real-time traffic data and historical transportation efficiency records. It is the transportation route with the shortest transportation time, the highest traffic stability, and the best transportation timeliness to match the demand for goods. It is the designated route for this allocation and transportation.

[0069] Physical attributes are a set of physical characteristics parameters inherent in out-of-stock goods, including physical characteristics that affect the choice of transportation means, such as weight, volume, packaging form, fragility, temperature control requirements, and stacking restrictions.

[0070] Shelf life is extracted from the product's expiration date. It is the remaining salable time for out-of-stock products from the current time point until the product's expiration date. It is a core parameter for measuring product freshness and determining transportation timeliness requirements.

[0071] Transportation vehicles are vehicles used to transport out-of-stock goods between outgoing outlets and out-of-stock outlets. They include different types of freight vehicles such as refrigerated trucks, ambient temperature vans, small delivery vans, and same-city instant delivery vehicles.

[0072] The transit time cost is calculated based on the mileage of the optimal route, real-time traffic status, and historical transportation efficiency. It is the cost corresponding to the time required to complete the transportation of this route, including the cost of transportation personnel's working hours, vehicle usage time, and potential losses due to time delays.

[0073] Transportation vehicle adaptation costs are the additional costs incurred in selecting appropriate transportation vehicles to match the physical attributes and shelf life of out-of-stock goods. These costs include the temperature control costs of refrigerated trucks, special protective packaging costs, rental and usage costs of special vehicle models, and the cost of using compliant freight qualifications.

[0074] Route usage cost is the fixed and variable toll costs incurred in completing the optimal route of transportation, including direct costs related to vehicle travel such as highway tolls, urban road freight tolls, parking fees, and fuel / electricity costs.

[0075] Transportation costs are calculated by integrating travel time costs, transportation vehicle adaptation costs, and route usage costs. The total cost incurred in completing this temporary allocation and transportation activity is a core component of subsequent comprehensive scheduling cost accounting.

[0076] Furthermore, firstly, all passable transportation routes of all network points and corresponding out-of-stock network points are retrieved in a targeted manner, and the actual passage conditions of each transportation route are collected simultaneously. Routes that do not meet the requirements for freight passage are eliminated, and multiple complete candidate transportation routes are generated by combining them.

[0077] Subsequently, the physical attributes and remaining shelf life of the out-of-stock goods in this allocation are extracted, compliant transportation vehicles that meet the requirements for goods transportation protection and timeliness are matched, and real-time traffic data and historical transportation efficiency records of the corresponding candidate transportation routes are retrieved. The optimal transportation route is selected through a comprehensive evaluation of timeliness and stability.

[0078] Finally, the travel time cost corresponding to the optimal route, the adaptation cost of the selected transportation vehicle, and the fixed route usage cost corresponding to the route are calculated separately. The three cost items are summarized and integrated to finally calculate the total transportation cost corresponding to this temporary transfer.

[0079] For example, for outlet A, which sells room-temperature yogurt and is experiencing stock shortages, a candidate transport set including outlets B and C with slow-moving stock is formed after screening. First, all passable transport routes between outlets B and C and outlet A are extracted. Then, considering the actual traffic conditions such as truck restrictions, road construction status, and number of lanes for each route, routes where trucks are prohibited are eliminated, generating 3 candidate transport routes from outlet B to outlet A and 2 candidate transport routes from outlet C to outlet A.

[0080] Subsequently, real-time traffic congestion data, historical transportation time and on-time rate during the morning peak hours, and other historical transportation efficiency records of the five candidate transportation routes were retrieved. After comprehensive evaluation, the shortest delivery route from point B to point A and the shortest delivery route from point C to point A were selected as the two optimal routes. At the same time, the room temperature sealing and stacking physical properties of the room temperature yogurt products to be transferred, as well as the remaining 45-day shelf life, were extracted to match suitable room temperature van delivery trucks as transportation tools.

[0081] Finally, the travel time cost of the two optimal routes, the transportation vehicle adaptation cost of the normal temperature box truck, and the route usage costs such as fuel and parking fees for the corresponding routes were calculated separately. After integrating the three costs, the transfer transportation cost from point B to point A was calculated to be 120 yuan, and the transfer transportation cost from point C to point A was 180 yuan, thus completing the full calculation of the transfer transportation cost.

[0082] In this embodiment, calculating the lost sales opportunity value of the slow-moving outlets during the replenishment cycle includes: Based on the historical sales records of the slow-moving outlets, the daily average sales and actual sales volatility of the out-of-stock products are extracted to predict the expected sales trend of the out-of-stock products during the replenishment cycle. Analyze the inventory turnover rate of the substitute products for the out-of-stock items during the replenishment cycle, analyze the potential loss opportunities of the out-of-stock items, and combine the potential loss opportunities with the expected sales trend to obtain the sales opportunity loss value caused by temporary scheduling.

[0083] Specifically, Historical transaction records are full-volume structured transaction details generated by all sales activities of slow-moving products at each outlet within a predetermined operating cycle. They are the core basic parameters for calculating product sales rate and predicting sales trends, and are obtained through the POS sales system and online transaction system of the sales outlets.

[0084] The average daily sales value is extracted from the historical sales records of slow-moving outlets. It is the average daily sales volume of out-of-stock products within a fixed statistical period. It is a core basic indicator that reflects the daily sales rate of products and predicts the sales scale within the replenishment period. The statistical period can be set to daily, weekly, monthly, or other dimensions according to the characteristics of product categories.

[0085] Actual sales volatility is calculated based on historical sales records of slow-moving outlets. It measures the fluctuation range of the actual daily sales volume of out-of-stock products from the daily average sales. It is a core parameter for quantifying the stability of product sales and correcting expected sales trends. The higher the volatility, the stronger the uncertainty of product sales.

[0086] The expected sales trend is a prediction of the sales volume trend and expected total sales volume of a product during the corresponding replenishment cycle, which is obtained by combining the daily average sales of out-of-stock products with the actual sales volatility. It is the core benchmark data for calculating lost sales opportunities.

[0087] Alternative goods are products of the same category that are highly similar to out-of-stock products in terms of function, price, and consumption scenarios. They can meet the same needs of consumers and can be purchased by consumers when out-of-stock products are out of stock. They are a core reference indicator for assessing the probability of customer churn.

[0088] Inventory turnover rate is the sales volume of substitute goods per unit time during the replenishment cycle. It is a core indicator that reflects the sales speed of substitute goods and quantifies the degree of consumer demand shift. The faster the turnover rate, the higher the probability that consumers will switch to substitute goods.

[0089] Potential lost opportunities are a quantitative indicator that represents the probability and potential revenue loss of lost orders and customers switching to alternative products or other outlets due to the stock shortage of out-of-stock products during the replenishment cycle. It is a core component of the sales opportunity loss value.

[0090] The sales opportunity loss value is a numerical indicator that quantifies the potential sales revenue that slow-moving outlets may lose during the replenishment cycle due to the temporary transfer of surplus out-of-stock goods to out-of-stock outlets. It is a core component of the overall dispatch cost accounting. The higher the value, the greater the sales revenue loss incurred by the outlets that were transferred.

[0091] Furthermore, firstly, from the historical sales records of the target slow-moving outlets, the daily average sales and actual sales volatility of the corresponding out-of-stock products are extracted, and based on the two core sales data, the expected sales trend of the out-of-stock products in the corresponding replenishment cycle is predicted. Further targeted analysis is conducted on the inventory digestion rate of substitute products for the out-of-stock item within the corresponding replenishment cycle. Based on the inventory digestion rate of substitute products, a quantitative analysis of the potential loss opportunities generated after the out-of-stock item is transferred out is completed. Finally, the quantified potential loss opportunities are integrated with the previously generated expected sales trends to output the sales opportunity loss value corresponding to this cross-site temporary transfer.

[0092] For example, outlet A is out of stock of ambient yogurt, while outlets B and C are experiencing slow sales of the same product. Both outlets have been included in the candidate list for this restocking. The pre-set replenishment period for this ambient yogurt is 7 days. The system first extracts the historical sales records of outlet B for the past 30 days, calculating the average daily sales of the ambient yogurt to be 8 boxes, with an actual sales volatility of 15%. Based on these two data points, the system predicts a stable sales trend of 56 boxes for this product within the 7-day replenishment period.

[0093] The system then analyzed that the substitute product for the room-temperature yogurt was a room-temperature lactic acid bacteria beverage of the same specification and price. The inventory turnover rate of this substitute product at outlet B over the past 30 days was 7 boxes per day. Based on this turnover rate, it was found that if the surplus inventory of the room-temperature yogurt were transferred out, outlet B would have a 30% chance of losing orders during the replenishment cycle. Finally, by combining the potential loss opportunity with the expected sales trend, the sales opportunity loss caused by this temporary transfer at outlet B was calculated to be the quantitative amount of sales revenue corresponding to 16.8 boxes.

[0094] Simultaneously complete the corresponding calculations for point C, extract the historical transaction records of point C for the past 30 days, calculate that the average daily sales of the room temperature yogurt is 5 boxes, the actual sales volatility is 10%, the expected sales trend within the 7-day replenishment cycle is 35 boxes that can be sold, analyze that the inventory digestion rate of the same specification alternative products is 4 boxes per day, and find that the potential loss opportunity is a 20% probability of order loss.

[0095] The final calculation shows that the sales opportunity loss caused by this temporary allocation at point C is the quantified amount of sales revenue corresponding to 7 boxes. These two values ​​will be simultaneously included in the overall scheduling cost accounting of the corresponding point, providing core data support for the selection of the optimal allocation plan.

[0096] In this embodiment, generating a discount amount based on the shelf life of the out-of-stock product includes: The shelf life of the out-of-stock products is divided according to the length of time, and a discount coefficient is assigned to each interval. The historical sales speed and inventory digestion cycle of the out-of-stock products are analyzed to generate the slow-moving factor of the out-of-stock products. By combining the slow-moving factor and the discount coefficient, and associating them with the initial cost of the out-of-stock goods, a discount amount for the out-of-stock goods is generated.

[0097] Specifically, the shelf life is extracted from the product's expiration date. The remaining salable time for out-of-stock products from the current time point to the product's expiration date is the core time parameter for measuring product freshness and classifying near-expiration levels. It is obtained through the linkage between the brand's product master data management system and the real-time inventory system of each sales outlet.

[0098] The cycle interval is a continuous time segment formed by standardizing the shelf life of out-of-stock products based on the industry's near-expiry grading rules for the product category and brand management requirements. It is the core carrier for grading the degree of near-expiry of products.

[0099] The discount factor is a price discount ratio preset for each period interval that is positively correlated with the degree of near expiration of the product. The higher the degree of near expiration of the product, the larger the corresponding discount factor. It is the core ratio parameter for calculating the discount amount of product transfer. It is uniformly set by the brand supply chain management department and the finance department in combination with the category gross profit level and the rules for handling near-expiration losses and is entered into the product master data system.

[0100] Historical sales speed is extracted from the historical sales records of slow-moving outlets. It is the average sales volume of out-of-stock products per unit time within a fixed statistical period. It is a core indicator for quantifying the daily sales capacity of products and determining the degree of slow-moving products. The statistical period can be set to daily, weekly, or monthly dimensions according to the characteristics of product categories.

[0101] The slow-moving factor is calculated based on the historical sales speed and inventory digestion cycle of out-of-stock products. It is a numerical indicator that quantifies the degree of slow-moving and stockpiling of products. The higher the value, the weaker the product's sales ability and the higher the risk of slow-moving and stockpiling. It is the core parameter for dynamically adjusting the discount coefficient and can accurately match the actual slow-moving situation of different outlets and different products.

[0102] Initial cost is the basic unit cost of purchasing and warehousing out-of-stock goods. It includes fixed cost items such as the purchase price of the goods and the allocated costs of warehousing logistics. It is the base parameter for calculating the discount amount and is obtained from the brand supply chain procurement management system and the product master data system.

[0103] The discount amount is calculated by combining the degree of near expiration and slow-moving inventory of the goods with the basic procurement cost. The unit price discount amount and the total discount amount of the corresponding transfer volume when goods are transferred across outlets are the core pricing parameters for balancing the interests of the transferring and receiving outlets and revitalizing near-expiration and slow-moving inventory. At the same time, it is also a core component of the comprehensive cost accounting of multi-outlet transfer and scheduling.

[0104] Furthermore, the shelf life of out-of-stock products is first retrieved, and the shelf life is divided into multiple consecutive period intervals based on the brand's pre-set near-expiration grading rules. Each completed period interval is matched and assigned a pre-set corresponding discount coefficient.

[0105] Simultaneously, retrieve the complete historical sales records of the out-of-stock product at the corresponding slow-moving outlets, calculate the historical sales speed of the product, and combine it with the already calculated inventory digestion cycle of the product to complete the quantitative calculation and generation of the slow-moving factor.

[0106] The generated slow-moving factor is then integrated with the discount coefficient of the corresponding period interval to achieve dynamic adjustment of the discount ratio. The initial cost base of the out-of-stock product is then linked to complete the standardized calculation and generation of the unit discount amount of the out-of-stock product and the total discount amount of the corresponding transfer volume.

[0107] The integrated calculation method first uses a slow-moving factor, which characterizes the actual slow-moving nature of goods, to dynamically adjust the basic discount coefficient preset according to the shelf life range. The more severe the slow-moving backlog and the weaker the daily sales ability, the higher the final discount ratio after adjustment. Then, the adjusted final discount ratio is multiplied by the unit initial purchase cost of the corresponding goods to calculate the discount amount per unit of goods. Finally, combined with the total amount of surplus inventory that can be transferred at the outlet, the total discount amount corresponding to this transfer is calculated, and this amount will be directly included in the comprehensive transfer cost accounting system of the corresponding outlet.

[0108] For example, outlet A, which is out of stock of room-temperature yogurt, and outlets B and C, which are experiencing slow sales of the same product, have been included in the candidate list for this transfer. The total shelf life of this room-temperature yogurt is 6 months, and the brand has pre-defined four shelf-life intervals: more than 90 days remaining, 60-90 days, 30-60 days, and less than 30 days remaining, with corresponding discount rates of 0%, 5%, 15%, and 35%, respectively.

[0109] First, the remaining shelf life of this room-temperature yogurt at outlet B is retrieved, which is 42 days, falling within the 30-60 day cycle range, and a corresponding discount factor of 15% is applied. At the same time, the historical sales data of this product at outlet B for the past 30 days is retrieved, and the historical sales speed of this product is calculated to be an average of 8 boxes per day. Combined with the 22-day inventory digestion cycle of this product at outlet B, the slow-moving factor of this product is calculated to be 1.2.

[0110] By combining the slow-moving factor of 1.2 with the discount coefficient of 15%, the adjusted discount ratio is 18%. Then, by linking the initial unit cost of the product of 30 yuan / box, the final calculation shows that the unit discount amount of the product is 5.4 yuan / box. The total discount amount corresponding to the 55 boxes of surplus inventory that can be allocated this time is 297 yuan.

[0111] Simultaneously, the discount calculation for this product at outlet C was completed. The remaining shelf life of this room-temperature yogurt at outlet C was retrieved as 58 days, falling within the 30-60 day cycle range, with a matching discount coefficient of 15%. The historical sales speed of this product at outlet C was retrieved as an average of 5 boxes per day. Combined with a 22-day inventory digestion cycle, a slow-moving factor of 1.1 was generated. After integration, the adjusted discount ratio was 16.5%. With an initial unit cost of 30 yuan / box, the calculated unit discount was 4.95 yuan / box. The total discount corresponding to the 35 boxes of surplus inventory available for allocation this time is 173.25 yuan. These two discount amounts will be simultaneously incorporated into the overall scheduling cost accounting process for the corresponding outlet, providing core data support for selecting the optimal allocation plan.

[0112] Cost fusion module 105: Fuses the transportation cost, the sales opportunity loss value and the discount amount to obtain the comprehensive scheduling cost of each network point in the candidate transfer center, and selects the candidate scheme with the minimum comprehensive scheduling cost to generate a suggested transfer instruction; In this embodiment, the process of integrating the transportation cost, the lost sales opportunity value, and the discount amount to obtain the comprehensive scheduling cost of each network point in the candidate transfer-out group, and selecting the candidate scheme with the minimum comprehensive scheduling cost to generate a suggested transfer instruction, includes: The transportation cost, the lost sales opportunity value, and the discount amount are normalized, and dynamic weights are assigned to the normalized transportation cost, the lost sales opportunity value, and the discount amount. The transportation cost after dynamic weight allocation, the lost sales opportunity value, and the discount amount are integrated, and the overall scheduling cost of each point in the candidate transfer set is calculated by weighted summation. Compare the overall scheduling costs of all outlets in the candidate transfer set, select the slow-moving outlet with the lowest cost as the transferor, and generate a suggested transfer instruction.

[0113] Specifically, normalization is a process that maps three indicators—transportation cost, sales opportunity loss value, and discount amount—that have significant differences in dimensions and numerical ranges to the same numerical range through a standardization method. This process is used to eliminate the differences in dimensions between different indicators, ensure the scientific nature of subsequent weight allocation and cost integration calculations, and adapt to the unified accounting needs of multi-dimensional costs in multi-outlet retail scenarios.

[0114] Dynamic weights are dynamically adjusted weight coefficients assigned to the three normalized cost indicators based on the business characteristics of the allocation scenario, the product category attributes, and the network operation priority. The sum of the weight coefficients is 1, which is used to distinguish the degree of influence of different cost items in the overall cost accounting of the allocation. It is dynamically configured by the brand supply chain management rules and business scenario requirements.

[0115] Weighted summation is a mathematical calculation method that sums up the three cost indicators after dynamic weight allocation, regional correction, and hierarchical processing, by multiplying them according to their corresponding weight coefficients. It is the core calculation logic for calculating the comprehensive cost of single network dispatch.

[0116] The overall dispatch cost is calculated using a weighted summation method. It represents the total quantified value of the overall cost and potential losses that a single candidate dispatching outlet must bear to complete this goods transfer. This value is the core criterion for evaluating the merits of different dispatching outlet transfer plans. The recommended transfer instruction is generated based on the optimal transferor selection results. It is a standardized transfer execution recommendation document that includes the transferor outlet, the receiving outlet with out-of-stock items, details of the transferred goods, transfer quantity, recommended transfer time, and details of comprehensive costs. It is the core basis for the negotiation and final transfer execution between the supply and demand outlets.

[0117] Furthermore, we first normalized the three core cost indicators—transportation costs, lost sales opportunities, and discounts—to eliminate the differences in dimensions and numerical ranges between the different indicators. Then, we assigned matching dynamic weights to the three normalized indicators based on the business scenario, product category attributes, and operational priorities of this allocation.

[0118] Subsequently, the transportation costs after weight allocation were verified for compliance, the sales opportunity loss value was adjusted regionally to suit the operating environment of the outlets, the discount amount was calibrated in a tiered manner based on the near-expiry level and the degree of slow sales, and then the comprehensive scheduling cost corresponding to each slow-selling outlet in the candidate transfer center was calculated one by one through a weighted summation calculation method.

[0119] Finally, the system iterates through the scheduling cost values ​​of all outlets in the candidate transfer set, completes a horizontal comparison of all values, and selects the slow-moving outlet with the lowest cost as the transferor for this transfer. Simultaneously, based on the full range of business and cost parameters of this optimal solution, a standardized suggested transfer instruction is generated.

[0120] For example, a chain convenience store brand has 35 directly operated sales outlets in the local area. Outlet A is out of stock of ambient yogurt, with a shortage of 120 boxes. After preliminary screening, outlets B and C, which are experiencing slow sales, are included in the candidate set for this allocation. The system first extracts the transportation cost of outlet B (120 yuan), the sales opportunity loss value of outlet B (672 yuan), and the discount amount of outlet C (180 yuan), the sales opportunity loss value of outlet C (280 yuan), and the discount amount of outlet C (173.25 yuan). The system performs min-max normalization on the three indicators, mapping all values ​​to a unified range of 0-1. Combining the fast-moving consumer goods attributes of ambient yogurt and the priority of revitalizing near-expiry products, the system assigns dynamic weights of 0.2, 0.3, and 0.5 to the normalized transportation cost, sales opportunity loss value, and discount amount, respectively.

[0121] After weighting and allocating the transportation costs, numerical verification was performed by combining the regional access rules for same-city delivery within the city. The sales opportunity loss value was regionalized by combining the community customer flow attributes of the areas where outlets B and C are located. The discount amount was calibrated by combining the near-expiration stratification of the remaining shelf life of the goods. Then, through the weighted summation calculation method, the comprehensive scheduling cost value of outlet B was calculated to be 0.72, and the comprehensive scheduling cost value of outlet C was 0.38.

[0122] A horizontal comparison of the overall scheduling costs of candidate outlets B and C was completed. It was confirmed that the overall scheduling cost of outlet C was lower, so outlet C was selected as the sender for this transfer. Finally, based on the full set of transfer parameters of outlet C, a standardized suggested transfer instruction was generated, which included outlet C as the sender, outlet A as the recipient, room temperature yogurt as the transfer product, 35 boxes as the transfer quantity, 3 days as the transfer time, and a detailed breakdown of the overall costs. This instruction was then pushed to both the supply and demand outlets for negotiation and confirmation.

[0123] The formula for calculating the overall scheduling cost of each network point in the candidate dispatch set is: This is the overall scheduling cost, representing the final output value of the formula. The smaller the value, the better the allocation plan.

[0124] These are dynamic weighting coefficients, corresponding to the business weights of transportation costs, lost sales opportunities, and discount amounts, respectively. They can be dynamically adjusted according to product category and operational priority, and the weight sum is always 1.

[0125] This is the normalization function, which uses the min-max normalization specified in the documentation: This eliminates the dimensional differences between different cost items.

[0126] It is the weighted and standardized allocation and transportation cost, representing the final contribution of transportation costs to the overall scheduling cost.

[0127] It is the travel time cost, which represents the time-related cost corresponding to the optimal transportation route, including working hours, time delay losses, etc.

[0128] This refers to the cost of adapting transportation vehicles to match the physical attributes and shelf life of the goods, including temperature control, protection, and vehicle rental.

[0129] It refers to the fixed toll costs associated with the transportation route, including fuel / electricity costs, highway tolls, parking fees, etc.

[0130] It represents the total cost of all transportation involved in a single inter-branch goods transfer, which is the sum of all direct and indirect transportation-related costs incurred in completing one such transfer.

[0131] This is the result of normalized transportation costs, indicating that the transportation costs of all candidate outgoing points are uniformly mapped to a normalized value using the min-max standardization method. Standardized values ​​for a numerical range are used to eliminate differences in the dimensions and magnitudes of different cost items.

[0132] It is the weighted and standardized value of sales opportunity loss, representing the final contribution of sales opportunity loss to the overall scheduling cost.

[0133] It is the sales volume of a product per unit of time, representing the average sales quantity of a product within a fixed period extracted from sales records.

[0134] It is the product replenishment cycle, which represents the brand's preset fixed replenishment interval time extracted from the product's shelf life.

[0135] It represents the probability of potential order loss for a product, calculated based on the inventory turnover rate of alternative products, and the probability of customer churn after the product is removed from the inventory.

[0136] It is the revenue per unit of sales of a commodity, representing the gross profit corresponding to the sale of a single commodity, and is used to quantify the amount of lost sales opportunities.

[0137] It represents the total amount of lost sales opportunities, indicating the total potential sales profit that slow-moving outlets may lose during the replenishment cycle due to the transfer of surplus goods to outlets with shortages.

[0138] This is the normalized result of the sales opportunity loss, indicating that the sales opportunity loss values ​​of all candidate outlets to be removed are uniformly mapped to... Standardized values ​​within a numerical range ensure fairness in the combined calculation of costs from multiple dimensions.

[0139] It is the weighted and standardized value of sales opportunity loss, representing the final contribution of sales opportunity loss to the overall scheduling cost.

[0140] It is the initial unit cost of a commodity, representing the basic cost of purchasing and warehousing a single commodity, including the purchase price and the allocated costs of warehousing logistics.

[0141] It is the near-expiry discount coefficient, which represents the preset discount ratio based on the remaining shelf life of the product. The higher the degree of near expiry, the larger the coefficient.

[0142] This represents the current available inventory of the product, indicating the compliant and salable remaining inventory of the product in the real-time inventory system of the outlet.

[0143] It is the reasonable turnover cycle of goods, which represents the industry-standard healthy turnover time extracted from the expiration date of goods.

[0144] It is the commodity slow-moving factor, which is a numerical indicator that quantifies the degree of slow-moving and stockpiling of commodities. The larger the value, the weaker the commodity's sales ability and the higher the risk of slow-moving and stockpiling. It is used to dynamically adjust the basic discount coefficient.

[0145] It refers to the quantity of goods that can be allocated, representing the surplus quantity that can be shipped out after subtracting the safety stock threshold from the inventory of slow-moving outlets.

[0146] It is the total discount amount for transfers, which represents the total price discount amount calculated based on the degree of near expiration and slow-moving inventory of goods when transferring across outlets. It is used to balance the interests of supply and demand and to revitalize near-expiration and slow-moving inventory.

[0147] This is the normalized result of the discount amount, indicating that the discount amounts of all candidate branches are uniformly mapped to... Standardized values ​​within a numerical range eliminate differences in the magnitude of values ​​for different cost items.

[0148] For example, a chain convenience store brand has 35 directly operated sales outlets in the local area, mainly selling standardized retail goods such as pre-packaged food, chilled dairy products, and daily necessities. This time, it conducted cross-outlet intelligent allocation for room-temperature yogurt products. Among them, outlet A was identified by the system as an outlet with a shortage of room-temperature yogurt products, with a shortage of 120 boxes and a delivery time of 3 days. After preliminary classification, labeling, and screening, outlets B and C were identified as outlets with slow-moving stock of this product, and both met the conditions for allocation, and were included in the candidate allocation set for this allocation.

[0149] Prior to this allocation, basic rules and general product parameters were pre-set. The core elements include: using the core calculation formula for the overall scheduling cost of this solution to select the optimal solution; combining this with the core operational priority of revitalizing near-expiry FMCG inventory; assigning dynamic weights of 0.2, 0.3, and 0.5 to transportation costs, lost sales opportunities, and discounts respectively, with a total weight sum of 1; and employing the patented min-max standardization method for normalization, mapping all cost indicators to... The unified numerical range; at the same time, the general parameters of the room temperature yogurt product are preset, the initial unit purchase cost is 30 yuan / box, the unit sales gross profit is 40 yuan / box, the brand's fixed replenishment cycle is 7 days, and the reasonable turnover cycle of the product in the fast-moving consumer goods industry is 15 days.

[0150] By connecting with the POS sales system, real-time inventory system, and product master data system of each outlet, the full business data collection and verification of outlets B and C within the candidate outflow set was completed. Specifically: For outlet B, the transit time cost for the ambient temperature yogurt is 40 yuan, the transportation tool adaptation cost is 50 yuan, and the route usage cost is 30 yuan. The average daily sales volume is 8 boxes / day, the potential order loss probability is 30%, the remaining shelf life of the product is matched with a 15% near-expiry basic discount coefficient, the current available inventory is 85 boxes, the preset safety stock threshold is 30 boxes, and the total available surplus inventory is 55 boxes. For outlet C, the transit time cost for the ambient temperature yogurt is 60 yuan, the transportation tool adaptation cost is 50 yuan, and the route usage cost is 70 yuan. The average daily sales volume is 5 boxes / day, the potential order loss probability is 20%, the remaining shelf life of the product is matched with a 15% near-expiry basic discount coefficient, the current available inventory is 60 boxes, the preset safety stock threshold is 25 boxes, and the total available surplus inventory is 35 boxes.

[0151] Based on the collected business data, the original value calculations for the three core cost items were completed. First, the total transportation cost of the entire allocation was calculated as follows: the total transportation cost from point B to point A was 40 yuan + 50 yuan + 30 yuan = 120 yuan, and the total transportation cost from point C to point A was 60 yuan + 50 yuan + 70 yuan = 180 yuan. Second, the total amount of lost sales opportunities was calculated as follows: the lost sales opportunities for point B corresponding to this allocation were 8 boxes / day × 7 days × 30% × 40 yuan / box = 672 yuan, and the lost sales opportunities for point C corresponding to this allocation were 5... Box / day × 7 days × 20% × 40 yuan / box = 280 yuan; Finally, the total discount amount for the transfer is calculated. First, the slow-moving factor of this product at outlet B is 1.2, and the slow-moving factor of this product at outlet C is 1.1. After calculation, the total discount amount corresponding to this transfer at outlet B is 30 yuan / box × 15% × 1.2 × 55 boxes = 297 yuan, and the total discount amount corresponding to this transfer at outlet C is 30 yuan / box × 15% × 1.1 × 35 boxes = 173.25 yuan.

[0152] After calculating the original values ​​of the three core cost items, the system performs min-max normalization on all values ​​to eliminate differences in the dimensions and magnitudes of different cost items. Specifically, for transportation costs, the normalized value is 0 for point B and 1 for point C; for sales opportunity loss, the normalized value is 1 for point B and 0 for point C; and for discounts, the normalized value is 1 for point B and 0 for point C. The system then substitutes preset dynamic weights and performs a weighted summation to complete the final calculation of the overall scheduling cost. The calculated overall scheduling cost for point B is 0.2×0 + 0.3×1 + 0.5×1 = 0.8, and for point C it is 0.2×1 + 0.3×0 + 0.5×0 = 0.2.

[0153] After the system completes the comprehensive cost calculation for all candidate outlets, it compares the comprehensive costs of outlets B and C. It confirms that outlet C's comprehensive cost of 0.2 is significantly lower than outlet B's 0.8, and thus outlet C is selected as the optimal sender for this allocation. Simultaneously, a standardized suggested allocation instruction is generated, including the sending outlet C, the receiving outlet A, the allocated product being room-temperature yogurt, the allocation quantity being 35 boxes, the allocation timeframe being 3 days, and a detailed breakdown of comprehensive costs. This instruction is then pushed to outlets A and C for negotiation and confirmation, completing the process for this intelligent allocation plan.

[0154] Intelligent allocation module 106: transmits the suggested allocation instruction to the corresponding out-of-stock outlets and slow-moving outlets, adjusts the suggested allocation instruction based on the feedback and negotiation requests from the out-of-stock outlets and slow-moving outlets, and transmits it again until both parties confirm and the allocation is executed.

[0155] In this embodiment, the step of adjusting the suggested transfer instruction and re-delivering it based on the feedback and negotiation requests from the out-of-stock outlets and the slow-moving outlets, until both parties confirm and the transfer is executed, includes: After the suggested allocation instruction is issued, the system collects the stock-out outlets' requests for adjustments to replenishment timeliness and their opinions on cost allocation from the slow-moving outlets, and packages them into a two-way feedback negotiation request data packet. Based on the conflict indicators in the feedback negotiation request data packet, the suggested allocation instruction is dynamically adjusted to generate the final allocation instruction confirmed by both parties.

[0156] Specifically, feedback negotiation requests are a collective term for the adjustment needs, revision opinions, and negotiation demands raised by outlets with shortages and slow-moving inventory in response to the various execution clauses in the allocation instructions after the allocation instructions are issued to both the supply and demand outlets. It is the core input item for the system to adjust the allocation plan and is collected through the system interaction port of the outlet terminal.

[0157] The need to adjust the replenishment timeliness is a request made by the out-of-stock outlet based on its own store's sales rhythm, the urgency of the inventory gap, and expected changes in customer traffic, in response to the adjustment request for the delivery time limit of the goods agreed in the suggested transfer instruction. The out-of-stock outlet submits the request to the intelligent transfer module through the interactive port of the store sales management system.

[0158] The proposed revisions to cost allocation are requests from slow-moving outlets based on their own operational costs for transferring out inventory, losses from merchandise discounts, and lost sales opportunities. These revisions address the allocation ratio, responsible party, and accounting method for the costs related to the transfer as stipulated in the suggested transfer instructions. The slow-moving outlets submit these requests to the intelligent transfer module through the interactive interface of the store inventory management system.

[0159] The two-way feedback negotiation request data packet is a structured data set formed by the system after standardizing the format conversion, field completion and compliance verification of the collected requests for replenishment timeliness of out-of-stock outlets and the opinions on cost allocation correction of slow-moving outlets. It is the core data carrier of the system's dynamic adjustment and allocation instructions, and contains core fields such as the unique codes of the supply and demand outlets, the details of the adjustment requests, the threshold of the corresponding indicators, and the submission time of the requests.

[0160] Conflict indicators are the core execution indicators in the two-way feedback negotiation request data packets where the demands of out-of-stock outlets and slow-moving outlets differ and cannot be matched. They include quantitative indicators such as allocation timeliness, cost sharing ratio, quantity of allocated goods, and allocation execution time, which reflect the differences in demands between the supply and demand sides. They are the core target parameters for the system to dynamically adjust the allocation plan.

[0161] The final allocation instruction is a standardized and executable allocation execution document that is jointly confirmed and effective by both the out-of-stock outlet and the slow-moving outlet after the dynamic adjustment and optimization of the allocation plan based on the conflict indicators in the two-way feedback negotiation request data packet. It is the only compliant execution basis for completing inventory allocation operations between outlets and includes all execution information such as the finally confirmed transfer-out / transfer-in outlet, details of the transferred goods, transfer quantity, transfer time, cost allocation rules, and execution time.

[0162] Furthermore, the suggested allocation instructions are first pushed synchronously to the terminal systems of the corresponding out-of-stock and slow-moving outlets. Then, the requests for replenishment timeliness adjustments submitted by out-of-stock outlets and the cost allocation correction opinions submitted by slow-moving outlets are continuously collected. After the collected two-way requests are standardized and processed, they are packaged into a two-way feedback negotiation request data package.

[0163] Next, the core content of the data packet is analyzed to identify and extract conflict indicators where supply and demand differ. Based on the core principles of optimizing the overall scheduling cost and maximizing the matching of supply and demand, the corresponding terms in the suggested transfer instructions are dynamically adjusted and optimized. The adjusted transfer instructions are then pushed back to the supply and demand outlets for confirmation. The feedback collection and instruction optimization actions are executed in a loop until both the out-of-stock outlets and the slow-moving outlets have completed instruction confirmation. Finally, a final transfer instruction with execution effect is generated, triggering the subsequent inventory transfer execution process.

[0164] For example, a chain convenience store brand has 35 directly operated sales outlets in the local area. Among them, outlet A is out of stock of room temperature yogurt products, with a shortage of 120 boxes. Outlet C has been selected as the transferor for this transfer, and a standardized transfer instruction has been generated and pushed to outlets A and C.

[0165] After the transfer order was issued, it was found that A, based on the expected peak customer flow on weekends, proposed to adjust the original 3-day transfer time to a replenishment time of 2 days. At the same time, it was found that C, based on the calculation of commodity discount costs and transportation costs, proposed to adjust the rule in the original order that A would bear all transportation costs, to a cost sharing of 7:3 between the two parties. After the system completed the standardization processing of the two requests, it packaged them into a two-way feedback negotiation request data package.

[0166] After parsing the data packet, two conflicting indicators, namely the transfer timeliness and cost sharing ratio, were identified. Based on the constraints of same-city delivery resources and scheduling costs, the transfer timeliness in the suggested transfer instruction was adjusted to delivery within 2 days. At the same time, the transportation cost sharing ratio was adjusted to 70% for point A and 30% for point C. The adjusted transfer instruction was generated and pushed to points A and C again. Both parties confirmed the adjusted instruction, and finally, the effective final transfer instruction was generated, triggering the execution process of the room temperature yogurt inventory transfer between points A and C.

[0167] like Figure 2 The diagram shown is a flowchart illustrating a multi-branch inventory sharing and intelligent allocation method according to an embodiment of the present invention. In this embodiment, the multi-branch inventory sharing and intelligent allocation method includes: Collect sales records and product expiration dates for each sales outlet; Based on the sales records of the sales outlets, the inventory digestion cycle of the sold goods is determined. The replenishment cycle and reasonable turnover cycle of the goods with the expiration date are compared with the inventory digestion cycle, and the sales outlets are marked as out-of-stock outlets and slow-moving outlets based on the comparison results. From the aforementioned slow-moving outlets, outlets holding out-of-stock goods and whose inventory levels exceed their own safety stock are selected to form a candidate transfer set; Analyze the transportation costs between the candidate centralized outlets and the out-of-stock outlets, calculate the sales opportunity loss value of the slow-moving outlets during the replenishment cycle, and generate a discount amount based on the shelf life of the out-of-stock goods. By integrating the transportation cost, the lost sales opportunity value, and the discount amount, the overall scheduling cost of each network point in the candidate transfer-out group is obtained, and the candidate scheme with the minimum overall scheduling cost is selected to generate a suggested transfer instruction; The suggested transfer order is sent to the corresponding out-of-stock outlets and slow-moving outlets. Based on the feedback and negotiation requests from the out-of-stock outlets and slow-moving outlets, the suggested transfer order is adjusted and sent again until both parties confirm and the transfer is executed.

[0168] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0169] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0170] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0171] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0172] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A multi-site inventory sharing and intelligent allocation system, characterized in that, The system includes: Data acquisition module: Collects sales records and expiration dates of goods sold at each sales outlet; Classification and labeling module: Based on the sales transaction records of the sales outlets, determine the inventory digestion cycle of the sold goods, compare the replenishment cycle of the time limit and the reasonable turnover cycle of the goods with the inventory digestion cycle respectively, and mark the sales outlets as out-of-stock outlets and slow-moving outlets according to the comparison results respectively; Product screening module: Screens out outlets that hold out-of-stock products and whose inventory is higher than their own safety stock from the slow-moving outlets, forming a candidate transfer set; Cost calculation module: Analyzes the transportation costs between the candidate centralized outlets and the out-of-stock outlets, calculates the sales opportunity loss value of the slow-moving outlets during the replenishment cycle, and generates a discount amount based on the shelf life of the out-of-stock goods; Cost fusion module: It integrates the transportation cost, the lost sales opportunity value and the discount amount to obtain the comprehensive scheduling cost of each network point in the candidate transfer set, and selects the candidate scheme with the minimum comprehensive scheduling cost to generate a suggested transfer instruction; Intelligent allocation module: The suggested allocation instruction is sent to the corresponding out-of-stock outlets and slow-moving outlets. Based on the feedback and negotiation requests from the out-of-stock outlets and slow-moving outlets, the suggested allocation instruction is adjusted and sent again until both parties confirm and the allocation is executed.

2. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The step of determining the inventory clearance cycle of the sold goods based on the sales transaction records of the sales outlets includes: Extract the sales volume of the sold goods per unit time from the sales transaction record, and query the current inventory of the corresponding sold goods from the real-time inventory system of the sales outlet. Combine the sales volume per unit time with the current inventory to determine the inventory digestion cycle of the sold goods.

3. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The step of comparing the replenishment cycle and reasonable inventory turnover cycle of the aforementioned time limit with the inventory digestion cycle, and marking the sales outlets as out-of-stock outlets and slow-moving outlets based on the comparison results, includes: Extract the replenishment cycle and reasonable inventory turnover cycle of the sold goods from the aforementioned time limit; Compare the replenishment cycle with the inventory clearance cycle, analyze the stockout risk value of the sold goods, and determine the stockout locations of the sales outlets based on the stockout risk value; By comparing the reasonable turnover cycle of the goods with the inventory digestion cycle, the unsold risk value of the goods is analyzed, and the unsold risk value is used to determine whether the sales outlet is an unsold outlet.

4. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The step of selecting outlets from the slow-moving outlets that hold out-of-stock goods and whose inventory levels exceed their own safety stock, forming a candidate transfer set, includes: Based on the list of out-of-stock items at the out-of-stock outlets, filter all the inventory data of the slow-moving outlets, and match the list of out-of-stock items with the inventory data one by one, and filter out the matching outlets that match the out-of-stock outlets from the slow-moving outlets; Obtain the safety stock threshold and inventory quantity of the out-of-stock items in the list of out-of-stock items from the matching outlets, compare the safety stock threshold and the inventory quantity, retain outlets where the safety stock threshold is greater than the inventory quantity, and package them into a candidate recall set.

5. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The analysis of transportation costs between the candidate centralized distribution points and the out-of-stock distribution points includes: Extract the transportation routes between each outlet in the candidate dispatch set and the outlets experiencing stock shortages, and generate candidate transportation routes based on the actual traffic conditions of the transportation routes; Based on the physical properties and shelf life of the out-of-stock goods, select a suitable means of transportation for the out-of-stock goods, and select the optimal route from the candidate transportation routes by combining real-time traffic data and historical transportation efficiency records. The transportation cost generated by temporary scheduling is obtained by integrating the travel time cost, transportation vehicle adaptation cost, and route usage cost of the optimal route.

6. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The calculation of the lost sales opportunity value of the slow-moving outlets during the replenishment cycle includes: Based on the historical sales records of the slow-moving outlets, the daily average sales and actual sales volatility of the out-of-stock products are extracted to predict the expected sales trend of the out-of-stock products during the replenishment cycle. Analyze the inventory turnover rate of the substitute products for the out-of-stock items during the replenishment cycle, analyze the potential loss opportunities of the out-of-stock items, and combine the potential loss opportunities with the expected sales trend to obtain the sales opportunity loss value caused by temporary scheduling.

7. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The step of generating a discount based on the shelf life of the out-of-stock goods includes: The shelf life of the out-of-stock products is divided according to the length of time, and a discount coefficient is assigned to each interval. The historical sales speed and inventory digestion cycle of the out-of-stock products are analyzed to generate the slow-moving factor of the out-of-stock products. By combining the slow-moving factor and the discount coefficient, and associating them with the initial cost of the out-of-stock goods, a discount amount for the out-of-stock goods is generated.

8. The multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The method integrates the transportation cost, the lost sales opportunity value, and the discount amount to obtain the comprehensive scheduling cost of each network point in the candidate transfer-out group, and selects the candidate scheme with the minimum comprehensive scheduling cost to generate a suggested transfer instruction, including: The transportation cost, the lost sales opportunity value, and the discount amount are normalized, and dynamic weights are assigned to the normalized transportation cost, the lost sales opportunity value, and the discount amount. The transportation cost after dynamic weight allocation, the lost sales opportunity value, and the discount amount are integrated, and the overall scheduling cost of each point in the candidate transfer set is calculated by weighted summation. Compare the overall scheduling costs of all outlets in the candidate transfer set, select the slow-moving outlet with the lowest cost as the transferor, and generate a suggested transfer instruction.

9. A multi-site inventory sharing and intelligent allocation system as described in claim 1, characterized in that, The step of adjusting the suggested transfer instruction and re-delivering it based on feedback and negotiation requests from the out-of-stock outlets and the slow-moving outlets, until both parties confirm and the transfer is executed, includes: After the suggested allocation instruction is issued, the system collects the stock-out outlets' requests for adjustments to replenishment timeliness and their opinions on cost allocation from the slow-moving outlets, and packages them into a two-way feedback negotiation request data packet. Based on the conflict indicators in the feedback negotiation request data packet, the suggested allocation instruction is dynamically adjusted to generate the final allocation instruction confirmed by both parties.

10. A method for multi-site inventory sharing and intelligent allocation, characterized in that, The method includes: Collect sales records and product expiration dates for each sales outlet; Based on the sales records of the sales outlets, the inventory digestion cycle of the sold goods is determined. The replenishment cycle and reasonable turnover cycle of the goods with the expiration date are compared with the inventory digestion cycle, and the sales outlets are marked as out-of-stock outlets and slow-moving outlets based on the comparison results. From the aforementioned slow-moving outlets, outlets holding out-of-stock goods and whose inventory levels exceed their own safety stock are selected to form a candidate transfer set; Analyze the transportation costs between the candidate centralized outlets and the out-of-stock outlets, calculate the sales opportunity loss value of the slow-moving outlets during the replenishment cycle, and generate a discount amount based on the shelf life of the out-of-stock goods. By integrating the transportation cost, the lost sales opportunity value, and the discount amount, the overall scheduling cost of each network point in the candidate transfer-out group is obtained, and the candidate scheme with the minimum overall scheduling cost is selected to generate a suggested transfer instruction; The suggested transfer order is sent to the corresponding out-of-stock outlets and slow-moving outlets. Based on the feedback and negotiation requests from the out-of-stock outlets and slow-moving outlets, the suggested transfer order is adjusted and sent again until both parties confirm and the transfer is executed.

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