Supply chain strategy determination method, medium, apparatus, and computing device

Abstract

Embodiments of the present disclosure provide a supply chain strategy determination method, medium, device and computing device. The method comprises: based on a target strategy type, inputting supply chain key data and a preset strategy parameter group into a simulation model of the target strategy type, and outputting inventory characteristic data; based on the predicted inventory characteristic data, calculating a corresponding evaluation index; determining that the evaluation index meets a preset value, and determining a supply chain strategy based on the preset strategy parameter group, the inventory characteristic data and the target strategy type. The method solves the problem that the supply chain strategy of the full link cannot be uniformly calculated in the related art, resulting in insufficient reliability of the supply chain strategy, and significantly improves the efficiency and reliability of the supply chain strategy.

Description

Technical Field

[0001] The embodiments of this disclosure relate to the field of supply chain inventory management technology, and more specifically, the embodiments of this disclosure relate to a supply chain strategy determination method, medium, apparatus and computing device. Background Technology

[0002] This section is intended to provide background or context for the embodiments of this disclosure as set forth in the claims. The description herein is not intended to be a prior art simply because it is included in this section.

[0003] With the development of e-commerce and the improvement of people's living standards, consumers have higher requirements for the quality and response speed of e-commerce logistics and delivery services. In the e-commerce field, the supply chain mainly includes e-commerce platforms, retail stores on e-commerce platforms, suppliers, warehouses, and logistics providers.

[0004] In e-commerce logistics and delivery, the entire supply chain process involves upstream suppliers setting up directly operated stores or brand retail stores on e-commerce platforms. Consumers place orders on these platforms, which then forward the orders to third-party logistics companies for storage and transportation. The product flow process involves upstream suppliers' production facilities entering the third-party logistics companies' warehouses in various locations before the products are shipped out to consumers according to the orders.

[0005] Among these factors, the timing of warehouse orders and the quantity of different types of goods stored have the greatest impact on the overall performance of the entire supply chain. Therefore, accurately assessing supply chain strategies is crucial for ensuring the performance of the entire supply chain.

[0006] However, the end-to-end supply chain strategy is affected by multiple factors such as demand uncertainty, logistics uncertainty, supplier uncertainty, and inventory cycle. Moreover, the time cycle is long and the amount of calculation is huge. In actual operation, it is impossible to uniformly calculate the end-to-end strategy, which makes it difficult to control the overall performance of the supply chain in the entire region. Summary of the Invention

[0007] This disclosure provides a method, medium, apparatus, and computing device for determining supply chain strategies, in order to solve the problem that the supply chain strategy cannot be uniformly calculated across the entire chain in related technologies, resulting in insufficient reliability of the supply chain strategy.

[0008] In a first aspect of this disclosure, a method for determining a supply chain strategy is provided, comprising:

[0009] Based on the target strategy type, key supply chain data and preset strategy parameter groups are input into the simulation model of the target strategy type, and inventory characteristic data is output. Key supply chain data includes historical supply chain indicator data, current inventory data and predicted sales data. The strategy parameter group is used to represent the strategy parameters corresponding to the set links of the supply chain.

[0010] Based on the predicted inventory characteristics data, calculate the corresponding evaluation indicators;

[0011] Determine if the evaluation indicators meet the preset values, and determine the supply chain strategy based on the preset strategy parameter set, inventory characteristic data, and target strategy type.

[0012] In one embodiment of this disclosure, historical supply chain indicator data includes at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data, and historical stockout rate for each type of commodity; current inventory data includes at least one of the following: current inventory commodity type, quantity, seasonal attributes, and inventory classification; and predicted sales data includes at least one of the following: predicted sales volume, predicted activity sales volume, and predicted activity data for each type of commodity.

[0013] In one exemplary embodiment of this disclosure, the strategy parameter set includes at least one of the following: the replenishment frequency and procurement cycle corresponding to the warehouse, the minimum order quantity corresponding to the supplier, and the safety stock days corresponding to the product.

[0014] In one exemplary embodiment of this disclosure, the target strategy type includes a replenishment strategy, an arrival strategy, and an inventory balancing strategy. Determining the supply chain strategy based on a preset strategy parameter set, inventory characteristic data, and the target strategy type includes: if the target strategy type is a replenishment strategy, calculating the replenishment quantity corresponding to the warehouse at each time point based on the preset strategy parameter set and inventory characteristic data; if the target strategy type is an arrival strategy, calculating the time point when the supplier should replenish, the replenishment time, and the corresponding warehouse based on the preset strategy parameter set and inventory characteristic data; if the target strategy type is an inventory balancing strategy, determining the inventory quantity corresponding to each warehouse at each time point based on the preset strategy parameter set and inventory characteristic data.

[0015] In one exemplary embodiment of this disclosure, based on a target strategy type, key supply chain data and a preset set of strategy parameters are input into a simulation model of the target strategy type to output predicted inventory characteristic data. This includes: inputting key supply chain data and a preset set of strategy parameters into a simulation model of the target strategy type to obtain a strategy output for a unit of time; inputting the strategy output into the simulation model of the target strategy type to obtain a strategy output for the next unit of time; repeating the step of obtaining the strategy output for the next unit of time until the total time corresponding to the strategy output is equal to a set cycle length; and using the strategy output as predicted inventory characteristic data.

[0016] In one exemplary embodiment of this disclosure, the inventory characteristic data includes inventory data and sales data; based on the inventory characteristic data, the corresponding evaluation index is calculated, including: based on the inventory data and sales data, calculating the stockout rate for each product in each warehouse.

[0017] In an exemplary embodiment of this disclosure, after calculating the corresponding evaluation index based on the inventory characteristic data, the method further includes: if the evaluation index does not meet the preset value, resetting the strategy parameter group and inputting it together with the supply chain key data into the simulation model of the target strategy type to obtain the corresponding inventory characteristic data; determining the evaluation index corresponding to the inventory characteristic data; repeating the steps of resetting the strategy parameter group until the corresponding evaluation index is calculated until the set conditions are met; and determining the supply chain strategy based on the strategy parameter group, inventory characteristic data and target strategy type corresponding to the set conditions being met.

[0018] In one exemplary embodiment of this disclosure, the setting conditions include at least one of the following: the number of times the strategy parameter group is repeatedly set reaches a set number; the index corresponding to the strategy parameter group meets a preset value.

[0019] In a second aspect of this disclosure, a computer-readable storage medium is provided, comprising:

[0020] The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, are used to implement the supply chain strategy determination method as described in the first aspect of this disclosure.

[0021] In a third aspect of this disclosure, a supply chain strategy determination apparatus is provided, comprising:

[0022] The simulation module is used to input key supply chain data and preset strategy parameter groups into the simulation model of the target strategy type based on the target strategy type, and output inventory characteristic data. The key supply chain data includes historical supply chain indicator data, current inventory data and predicted sales data. The strategy parameter group is used to represent the strategy parameters corresponding to the set links of the supply chain.

[0023] The evaluation module is used to calculate corresponding evaluation indicators based on predicted inventory characteristic data;

[0024] The output module is used to determine whether the evaluation indicators meet the preset values ​​and to determine the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type.

[0025] In one exemplary embodiment of this disclosure, the simulation module includes: historical supply chain indicator data including at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data, and historical stockout rate for each type of commodity; current inventory data including at least one of the following: current inventory commodity type, quantity, seasonal attributes, and inventory classification; and predicted sales data including at least one of the following: predicted sales volume, predicted activity sales volume, and predicted activity data for each type of commodity.

[0026] In one exemplary embodiment of this disclosure, the simulation module includes: a strategy parameter group including at least one of the following: the replenishment frequency and procurement cycle corresponding to the warehouse, the minimum order quantity corresponding to the supplier, and the safety stock days corresponding to the product.

[0027] In an exemplary embodiment of this disclosure, the output module is specifically used for: when the target strategy type includes a replenishment strategy, an arrival strategy, and an inventory balancing strategy, if the target strategy type is a replenishment strategy, calculating the replenishment quantity corresponding to the warehouse at each time node based on a preset strategy parameter set and inventory characteristic data; if the target strategy type is an arrival strategy, calculating the time node, replenishment time, and corresponding warehouse that the supplier should replenish based on the preset strategy parameter set and inventory characteristic data; and if the target strategy type is an inventory balancing strategy, determining the inventory quantity corresponding to each warehouse at each time node based on the preset strategy parameter set and inventory characteristic data.

[0028] In an exemplary embodiment of this disclosure, the simulation module is specifically used to: input key supply chain data and a preset set of strategy parameters into a simulation model of the target strategy type based on the target strategy type to obtain a strategy output for a unit time; input the strategy output into the simulation model of the target strategy type to obtain a strategy output for the next unit time; repeat the step of obtaining the strategy output for the next unit time until the total time corresponding to the strategy output is the set cycle length, and use the strategy output as predicted inventory characteristic data.

[0029] In one exemplary embodiment of this disclosure, the evaluation module is specifically used for: inventory characteristic data including inventory data and sales data; and calculating the stockout rate for each product in each warehouse based on the inventory data and sales data.

[0030] In an exemplary embodiment of this disclosure, the output module is specifically used for: calculating the corresponding evaluation index based on the predicted inventory characteristic data; if the evaluation index does not meet the preset value, resetting the strategy parameter group and inputting it together with the key supply chain data into the simulation model of the target strategy type to obtain the corresponding inventory characteristic data; determining the evaluation index corresponding to the inventory characteristic data; repeating the steps of resetting the strategy parameter group until the corresponding evaluation index is calculated until the set conditions are met; and determining the supply chain strategy based on the strategy parameter group, inventory characteristic data and target strategy type corresponding to the set conditions being met.

[0031] In one exemplary embodiment of this disclosure, the output module includes: setting conditions including at least one of the following: the number of times the strategy parameter group is repeatedly set reaches a set number; the index corresponding to the strategy parameter group meets a preset value.

[0032] In a fourth aspect of this disclosure, a computing device is provided, comprising: at least one processor;

[0033] and memory that is communicatively connected to at least one processor;

[0034] The memory stores instructions that can be executed by at least one processor to cause the computing device to perform the supply chain strategy determination method as described in the first aspect of this disclosure.

[0035] The supply chain strategy determination method, medium, apparatus, and computing device according to embodiments of this disclosure input key supply chain data and a preset set of strategy parameters into a simulation model of the target strategy type, outputting inventory characteristic data. Based on predicted inventory characteristic data, corresponding evaluation indicators are calculated to determine if the evaluation indicators meet preset values. Finally, the supply chain strategy is determined based on the preset set of strategy parameters, inventory characteristic data, and the target strategy type. This approach uses historical indicator data, current inventory data, and predicted sales data of the entire supply chain as input data for analysis, enabling unified calculation of decisions across the entire chain, rather than being limited to calculations of a single module. It allows a single model to calculate complex supply chain strategies across the entire chain, significantly improving computational efficiency. Furthermore, by combining with the preset set of strategy parameters, the strategy can be adjusted according to needs to obtain the optimal supply chain strategy, thereby ensuring the overall efficiency of the supply chain is optimized. Attached Figure Description

[0036] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which:

[0037] Figure 1An application scenario diagram illustrating an embodiment of the present disclosure is shown schematically;

[0038] Figure 2 A flowchart illustrating a supply chain strategy determination method according to another embodiment of this disclosure is shown schematically;

[0039] Figure 3 A flowchart illustrating a supply chain strategy determination method according to yet another embodiment of this disclosure is shown.

[0040] Figure 4 A flowchart illustrating a supply chain strategy determination method according to another embodiment of the present disclosure is shown schematically;

[0041] Figure 5 A schematic diagram of the structure of a storage medium according to another embodiment of the present disclosure is shown;

[0042] Figure 6 A schematic diagram of the structure of a supply chain strategy determination apparatus according to another embodiment of the present disclosure is shown.

[0043] Figure 7 A schematic diagram of the structure of a computing device according to another embodiment of the present disclosure is shown.

[0044] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0045] The principles and spirit of this disclosure will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement this disclosure, and are not intended to limit the scope of this disclosure in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.

[0046] Those skilled in the art will recognize that embodiments of this disclosure can be implemented as a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0047] According to embodiments of this disclosure, a supply chain strategy determination method, medium, apparatus, and computing device are proposed.

[0048] In this document, it should be understood that the terminology used is for convenience of understanding only and does not imply any limitation on its meaning. Furthermore, any number of elements in the accompanying drawings is for illustrative purposes only and not for limitation, and any naming is for distinction only and has no limiting meaning.

[0049] The following is a description of the terminology used in this disclosure:

[0050] Strategy parameter group: A collection of strategy parameters in each link of the supply chain. The strategy parameters are specific input values. By using the strategy parameters corresponding to each link (such as replenishment frequency), the supply chain strategy corresponding to each link (such as the strategy of the supplier link) can be determined.

[0051] Target Strategy Types: Different stages of the supply chain will have different objectives, which are called target strategy types. For example, the target strategy type for a warehouse might be to reduce the storage time of goods while ensuring a complete range of product types. Conversely, the target strategy type for a supplier only needs to consider delivery time or quantity, without needing to consider the storage conditions of goods in the warehouse.

[0052] The principles and spirit of this disclosure will be explained in detail below with reference to several representative embodiments. Invention Overview

[0054] The inventors have discovered that in current technology, logistics and distribution fields such as e-commerce rely heavily on the performance of the warehouse-centric supply chain. When the supply chain is efficient, goods sent by suppliers arrive at the warehouse in a timely and sufficient manner and are promptly delivered to the corresponding consumers, with shorter storage times. Conversely, when the supply chain is inefficient, the warehouse cannot replenish goods in a timely or sufficient manner, and goods cannot be delivered to consumers promptly, while goods also remain in the warehouse for excessively long periods. Therefore, determining appropriate supply chain strategies to optimize supply chain efficiency is of great significance to logistics and distribution fields such as e-commerce.

[0055] Since the entire supply chain includes multiple links from supplier delivery and warehouse receiving to external delivery, and each link has different strategy parameters, existing technologies usually model each link separately to determine the supply chain strategy for each link. This results in the strategy parameters of each link being relatively independent and the calculation cycle being long. When there is an error in a link, the overall error will be rapidly amplified due to the existence of multiple links, which severely limits reliability.

[0056] In this solution, key supply chain data across the entire chain are incorporated into the calculation, and a set of strategy parameters covering each link in the entire chain is used for evaluation to determine the supply chain strategy across the entire chain. This approach is highly efficient, has minimal error, and is highly reliable.

[0057] After introducing the basic principles of this disclosure, various non-limiting embodiments of this disclosure will be described in detail below.

[0058] Application Scenarios Overview

[0059] First refer to Figure 1 As shown, in the supply chain, warehouse 100 determines the frequency and quantity of goods to be obtained from supplier 110 based on the supply chain strategy, as well as the quantity and duration of goods stored in warehouse 100, and the speed and quantity of goods shipped to retailer 120 or user 130, thereby completing the logistics and distribution process of the supply chain.

[0060] It should be noted that, Figure 1 The scenario shown uses only one warehouse, supplier, goods, retailer, and user as an example for illustration, but this disclosure is not limited to this. That is to say, the number of warehouses, suppliers, goods, retailers, and users can be arbitrary.

[0061] Exemplary methods

[0062] The following is combined Figure 1 Application scenarios, refer to Figures 2 to 4 This document describes a method for determining supply chain strategies according to exemplary embodiments of the present disclosure. It should be noted that the above application scenarios are shown only to facilitate understanding of the spirit and principles of the present disclosure, and the embodiments of the present disclosure are not limited in any way. Rather, the embodiments of the present disclosure can be applied to any applicable scenario.

[0063] Figure 2 A flowchart illustrating a supply chain strategy determination method provided in one embodiment of this disclosure. Figure 2 As shown, the supply chain strategy determination method provided in this embodiment includes the following steps:

[0064] Step S201: Based on the target strategy type, input the key supply chain data and the preset strategy parameter group into the simulation model of the target strategy type, and output the inventory characteristic data.

[0065] Among them, key supply chain data includes historical supply chain indicator data, current inventory data, and forecasted sales data, while the strategy parameter group is used to represent the strategy parameters corresponding to the set links in the supply chain.

[0066] Specifically, because the factors and objectives considered by the target strategy type selected from different stages vary—for example, from the perspective of a retailer or user, the frequency of supplier shipments does not need to be considered, while from the supplier's perspective, the storage time of goods in the warehouse does not need to be considered—the model parameters of the simulation models corresponding to different target strategy types will differ. In practical use, it is necessary to first determine the target strategy to be analyzed, and then select the corresponding preset strategy parameter set based on the simulation model of that target strategy type for calculation.

[0067] The preset strategy parameter set consists of strategy parameters for each link initially determined based on key data of the supply chain. The preset strategy parameter set and key data of the supply chain are substituted into the simulation model for calculation. The feasibility of the preset strategy parameter set is evaluated based on the calculation results. If it is not feasible, the preset strategy parameter set is adjusted based on the evaluation results and substituted into the simulation model again for calculation until the adjusted strategy parameter set passes the evaluation.

[0068] The strategy parameters corresponding to each link in the preset strategy parameter group can be determined based on historical strategy parameter groups and key supply chain data. For example, if the sales volume of a certain product is around 3,000 units in the first quarter of each year, and the sales volume is average in each month, then the replenishment frequency in the strategy parameters corresponding to this product in the first quarter can be preset to once a month, and the minimum replenishment quantity can be preset to 1,000 units. Alternatively, if the current inventory data shows that the inventory of this product is 1,800 units, then the preset replenishment frequency can be set to once every 1.5 months, and the minimum replenishment quantity for each replenishment can be preset to 600 units.

[0069] The setup process can have different components depending on the division method, but it usually includes at least three links: supplier, warehouse, and consumer. The warehouse link can also be replaced by a distribution company. Retailers can also be included between the warehouse and the consumer, and manufacturers can also be included between the supplier and the warehouse. Each link has different strategy parameters, so they need to be discussed separately.

[0070] Inventory characteristic data corresponds to the current inventory data and represents the inventory data output by the simulation model after the end of the current period. It includes indicators such as the quantity of various goods stored in the warehouse and the storage time, and may also include advanced indicator data such as inventory fluctuation and stockout probability (which can be calculated by changes in the quantity of goods stored and sales).

[0071] Step S202: Calculate the corresponding evaluation indicators based on inventory characteristic data.

[0072] Specifically, after determining the simulation model for the target strategy type, the key supply chain data and the preset strategy parameter set are input into the simulation model, which will output the corresponding inventory characteristic data. Since the supply chain duration to be calculated in actual applications usually involves multiple cycles (e.g., if the total duration is a whole year, each month can be considered as a cycle), after obtaining the inventory characteristic data at the end of the current cycle, if the duration to be calculated still includes uncalculated cycles, the inventory characteristic data, historical supply chain indicator data, and predicted sales data will be used together as new key supply chain data. This data will be combined with the preset strategy parameter set and substituted back into the simulation model to calculate the next cycle. This process continues until all cycles are completed, and the final output result is the final inventory characteristic data.

[0073] Based on the final inventory characteristic data, the corresponding evaluation indicators can be calculated, such as the average storage time of a certain commodity (or the average storage time of all commodities in the warehouse stage), to determine whether the requirements are met.

[0074] Step S203: Determine if the evaluation indicators meet the preset values, and determine the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type.

[0075] Specifically, each evaluation indicator has a preset threshold (i.e., preset value). If the evaluation indicator meets the preset value (e.g., the calculated inventory fluctuation index is 0.5, which is less than the preset value of 0.6, so it is considered to meet the preset value), it can be considered that the preset strategy parameter set can meet the requirements of the target strategy type. Then, the supply chain strategy corresponding to the target strategy type can be determined based on the strategy parameter set. For example, when the target strategy type is a replenishment strategy, based on the replenishment frequency parameter value of 100 units / week in the strategy parameter set, the corresponding supply chain strategy is to apply for 100 units of replenishment from the supplier every week.

[0076] If the evaluation index does not meet the preset value, the preset strategy parameter group needs to be readjusted and then substituted into steps S201 to S202 for recalculation. For example, if the calculated inventory fluctuation index is 0.9, which is greater than the preset value of 0.6, it is considered that the preset value is not met. At this time, the replenishment frequency in the preset strategy parameter group can be shortened and the calculation can be recalculated.

[0077] According to the supply chain strategy determination method of this disclosure, key supply chain data and a preset set of strategy parameters are input into a simulation model of the target strategy type. Inventory characteristic data is output, and corresponding evaluation indicators are calculated based on predicted inventory characteristic data to determine if the evaluation indicators meet preset values. The supply chain strategy is then determined based on the preset set of strategy parameters, inventory characteristic data, and the target strategy type. This method uses historical indicator data, current inventory data, and predicted sales data of the entire supply chain as input data for analysis, enabling unified calculation of decisions across the entire chain, rather than being limited to calculations of a single module. This allows a single model to calculate complex supply chain strategies across the entire chain, significantly improving computational efficiency. Furthermore, by combining with the preset set of strategy parameters, the strategy can be adjusted according to needs to obtain the optimal supply chain strategy, thereby ensuring the overall efficiency of the supply chain is optimized.

[0078] Figure 3 A flowchart illustrating a supply chain strategy determination method provided in one embodiment of this disclosure. Figure 3 As shown, the supply chain strategy determination method provided in this embodiment includes the following steps:

[0079] Step S301: Based on the target strategy type, input the key supply chain data and the preset strategy parameter group into the simulation model of the target strategy type to obtain the strategy output per unit time.

[0080] Among them, key supply chain data includes historical supply chain indicator data, current inventory data, and forecasted sales data, while the strategy parameter group is used to represent the strategy parameters corresponding to the set links in the supply chain.

[0081] Specifically, the unit duration is a portion of the total supply chain duration to be calculated, and different unit durations can be selected depending on the situation. For example, if the calculation object is a warehouse inventory balancing strategy during peak seasons (such as shopping festivals), the goods turnover is relatively fast, and the unit duration can be 24 hours or three days (when shipping within the same city, the flow from warehouse to consumer and from supplier to warehouse can be completed in 24 hours; while under normal shipping conditions, the flow between each link can be completed in 72 hours). After each unit duration, the corresponding inventory data is determined based on the strategy parameter group and key supply chain data.

[0082] Since the inventory data obtained at this point is not the final output inventory characteristic data, it is named the strategy output, corresponding to the target strategy type. For example, if the target strategy type is the retailer's or consumer's delivery strategy, the strategy output can be the ordering strategy output; if the target strategy type is the supplier's replenishment strategy, the strategy output can be the transportation strategy output; if the target strategy type is the warehouse's inventory balancing strategy, then the strategy output is the warehouse capacity strategy output.

[0083] Furthermore, historical supply chain indicator data includes at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data, and historical stockout rate for each type of commodity; current inventory data includes at least one of the following: current inventory commodity type, quantity, seasonal attributes, and inventory classification; and predicted sales data includes at least one of the following: predicted sales volume, predicted activity sales volume, and predicted activity data for each type of commodity.

[0084] Specifically, current inventory categories include physical categories (e.g., large items, fragile items) and sales categories (e.g., cosmetics, electronic items). Seasonal attributes are used to indicate the sales distribution of goods in different seasons; for example, Christmas trees typically only have high sales in the fourth quarter, with extremely low sales in the other three quarters. Inventory grading is used to indicate the storability of goods, such as whether they are perishable items or not, and whether they can be stored in large quantities (e.g., customized goods cannot be stored in large quantities). Forecasted sales include expected sales (e.g., expected sales of 200,000 copies for a certain audio-visual product) and possible sales based on historical data (e.g., the sales of a certain shampoo can be used directly as the possible sales for the next quarter). Forecasted event sales are used to indicate sales during expected events (e.g., shopping festival events). Forecasted event data includes possible events and business models (e.g., group buying or bulk ordering).

[0085] In one embodiment of this solution, the strategy parameter group includes at least one of the following: the replenishment frequency and procurement cycle corresponding to the warehouse, the minimum order quantity corresponding to the supplier, and the safety stock days corresponding to the product.

[0086] Specifically, the replenishment frequency and procurement cycle of the warehouse have a significant impact on inventory fluctuations, the minimum order quantity of the supplier has a significant impact on the delivery frequency, and the safety stock days of the goods (which can be the shelf life or the expected storage time, such as frozen goods, although the actual storage time is long, the expected storage time is usually short, because the value will decrease after long-term storage).

[0087] Step S302: Input the strategy output into the simulation model of the target strategy type to obtain the strategy output for the next unit of time.

[0088] Specifically, in the next unit of time, the strategy output, along with the preset strategy parameter set, historical supply chain indicator data, and predicted sales data, is input into the simulation model to obtain the strategy output for the next market.

[0089] Step S303: Repeat the step of obtaining the strategy output for the next unit of time until the total time corresponding to the strategy output is the set cycle length, and use the strategy output as the predicted inventory characteristic data.

[0090] Specifically, after completing the entire total time loop, the final strategy output is used as the final output inventory feature data.

[0091] In one embodiment of this solution, inventory characteristic data includes inventory data and sales data.

[0092] Specifically, inventory characteristic data includes inventory data such as the inventory quantity and inventory fluctuations of each product in the warehouse, as well as sales data of each product.

[0093] Step S304: Based on inventory data and sales data, calculate the stockout rate for each product in each warehouse.

[0094] Specifically, the most important evaluation metric is the stockout rate, because stockouts have the greatest impact on the supply chain. Therefore, the stockout rate for each product can be calculated based on inventory and sales data.

[0095] In one embodiment of this solution, in addition to the stockout rate, the inventory volatility and / or inventory turnover rate of the goods are also included. This is because when the inventory volatility is high, stockouts are more likely to occur, and supply chain strategies need to be improved. On the other hand, when the inventory turnover rate (used to assess the turnover time of goods in the warehouse stage) is high, goods are more likely to remain in the warehouse for a long time, and supply chain strategies also need to be improved.

[0096] Step S305: If the target strategy type is a replenishment strategy, calculate the replenishment quantity for the warehouse at each time point based on the preset strategy parameter group and inventory characteristic data.

[0097] Specifically, depending on the type of target strategy, the specific data required for determining the supply chain strategy will also differ. For replenishment strategies, the most important data is the replenishment quantity at each time point.

[0098] The time node can be the unit of time in the aforementioned calculation, or it can be a unit smaller or larger than the unit of time. For example, if the unit of time is every 72 hours, the time node can be 24 hours, 72 hours, or weekly. Because the time for the warehouse to ship out is uncertain, the time for it to apply for replenishment can be very short (such as when the shipment volume and frequency are large) or very long (such as during the off-season).

[0099] The replenishment quantity can be calculated using the replenishment frequency and procurement cycle in the strategy parameter group, as well as the current inventory quantity and predicted sales volume in the key supply chain data.

[0100] In one embodiment of this solution, the replenishment strategy includes not only the replenishment quantity but also the replenishment frequency. When the shipment quantity and timing of goods are not fixed (such as goods limited to specific holidays), a specific replenishment frequency will also be determined. For example, for mooncakes, the replenishment frequency may be once a week during the period of three months to one month before the Mid-Autumn Festival, and once every two weeks during the period of one month before the Mid-Autumn Festival (because most people will choose to buy in advance). After the Mid-Autumn Festival, replenishment may not be necessary, as there is usually no need for replenishment at this time.

[0101] Step S306: If the target strategy type is a delivery strategy, calculate the time node, replenishment time and corresponding warehouse that the supplier should replenish based on the preset strategy parameter group and inventory characteristic data.

[0102] Specifically, the delivery strategy is a target strategy type determined based on the needs of retailers or users. Since retailers and users cannot store goods, the calculations need to cover the supplier's replenishment status and the warehouse where the replenishment arrives, so that the warehouse can ship the goods promptly upon receiving the retailer's or user's request. Additionally, because retailers or users are time-sensitive, the replenishment time also needs to be determined (e.g., for goods requiring temporary processing by the supplier, replenishment may take several business days after receiving the order).

[0103] The replenishment time required for each product between different suppliers and different warehouses is usually different. Therefore, it is necessary to calculate the replenishment time accordingly, or to calculate the average time for the product between different suppliers and different warehouses.

[0104] The timing of replenishment, the time required, and the warehouse can be calculated using the replenishment frequency, procurement cycle, minimum order quantity for suppliers, and key supply chain data such as the seasonal attributes of current inventory, historical inventory fluctuation data, historical stockout rate, and predicted sales data.

[0105] Step S307: If the target strategy type is an inventory balancing strategy, determine the inventory quantity corresponding to each warehouse at each time point based on the preset strategy parameter group and inventory characteristic data.

[0106] Specifically, the inventory balancing strategy is a target strategy type determined based on the warehouse stage. Ideally, the warehouse should ensure that the inventory fluctuations are not too large and that there are no shortages of any goods. Therefore, it is necessary to calculate the inventory level of each warehouse and adjust the replenishment of goods in the warehouse based on the inventory level.

[0107] Inventory levels can be calculated using the replenishment frequency, safety stock days for each product, and key supply chain data such as current inventory quantity, historical inventory data, historical stockout rate, and projected sales.

[0108] According to the supply chain strategy determination method of this disclosure, key supply chain data and a preset set of strategy parameters are input into a simulation model of the target strategy type to obtain a strategy output per unit time. This strategy output is then input back into the simulation model, and the process is repeated until the entire time period ends. Based on the output results, the stockout rate of goods is calculated, and the corresponding supply chain strategy is determined according to the target strategy type. Therefore, a full-link supply chain strategy can be provided for complex supply chains. Furthermore, since it eliminates the need for separate discussions of each stage, it can handle large amounts of data as output, improving the reliability and accuracy of the output supply chain strategy.

[0109] Figure 4 A flowchart illustrating a supply chain strategy determination method provided in one embodiment of this disclosure. Figure 4 As shown, the supply chain strategy determination method provided in this embodiment includes the following steps:

[0110] Step S401: Based on the target strategy type, input the key supply chain data and the preset strategy parameter group into the simulation model of the target strategy type, and output the inventory characteristic data.

[0111] Among them, key supply chain data includes historical supply chain indicator data, current inventory data, and forecasted sales data, while the strategy parameter group is used to represent the strategy parameters corresponding to the set links in the supply chain.

[0112] Step S402: Calculate the corresponding evaluation indicators based on inventory characteristic data.

[0113] Specifically, steps S401 to S402 and Figure 2 Steps S201 to S202 in the illustrated embodiment are the same and will not be repeated here.

[0114] Step S403: If the evaluation indicators do not meet the preset values, reset the strategy parameter group and input it together with the key supply chain data into the simulation model of the target strategy type to obtain the corresponding inventory characteristic data.

[0115] Specifically, if the values ​​in the strategy parameter group are set incorrectly, causing the evaluation indicators to fail to meet the preset values ​​(such as a high stockout rate), then the values ​​in the strategy parameter group need to be adjusted, and the calculation process from step S401 to step S402 needs to be repeated.

[0116] Depending on the specific circumstances of the numerical errors in the strategy parameter group and the degree of deviation between the evaluation indicators and preset values, the strategy parameter group can be adjusted in different ways. For example, if it is simply an input error, it can be adjusted to the correct value. If the settings are unreasonable and lead to a high stockout rate, parameters such as increasing the replenishment frequency need to be increased.

[0117] In one embodiment of this solution, the strategy parameter group can also be manually adjusted based on expert experience, with the strategy parameters adjusted through evaluation by relevant personnel.

[0118] Step S404: Determine the evaluation indicators corresponding to the inventory characteristic data.

[0119] Specifically, this step is related to step S402. Figure 2 The content of step S202 in the illustrated embodiment is the same, and will not be repeated here.

[0120] Step S405: Repeat the steps of resetting the strategy parameter group until the corresponding evaluation index is calculated, until the set conditions are met.

[0121] Specifically, if the strategy parameter set obtained after adjusting the parameters in sequence still fails to pass the test of the preset value, it is necessary to repeat the process of setting the strategy parameter set and substituting it into the simulation model for calculation until the corresponding evaluation index is calculated and evaluated.

[0122] In one embodiment of this solution, the set conditions include at least one of the following:

[0123] The number of times the strategy parameter group is repeatedly set reaches the set number;

[0124] The indicators corresponding to the strategy parameter group meet the preset values.

[0125] Specifically, since the strategy parameter group can only serve as a predictive guide, there may be situations where the corresponding indicators cannot meet the preset values ​​(if they do, the process should stop and output the results directly). The calculation will also end after the settings are adjusted a few times. If the set business target (predicted sales or predicted activity sales) differs significantly from historical sales data (e.g., the expected sales of a certain product are too high, exceeding the records), it may be impossible to guarantee that indicators such as the stockout rate meet the preset values ​​when combining the settings with historical supply chain indicators.

[0126] Step S406: Determine the supply chain strategy based on the strategy parameter group, inventory characteristic data and target strategy type corresponding to the conditions set.

[0127] Specifically, when the strategy parameter group meets the set conditions, the method for calculating the supply chain strategy can be referred to steps S305 to S307, which will not be repeated here.

[0128] According to the supply chain strategy determination method of this disclosure, key supply chain data and a preset set of strategy parameters are input into a simulation model of the target strategy type. Inventory characteristic data is output, and evaluation indicators are calculated based on the inventory characteristic data. If the evaluation indicators do not meet the preset values, the preset set of strategy parameters is adjusted, and the results are recalculated in the simulation model until the final result is obtained. Therefore, the strategy parameter set can be automatically optimized based on key supply chain data and business objectives, improving the feasibility and reliability of the supply chain strategy.

[0129] Exemplary media

[0130] After introducing the methods of exemplary embodiments of this disclosure, the following references are made. Figure 7 The storage medium of the exemplary embodiments of this disclosure will be described.

[0131] refer to Figure 5As shown, a program product 50 for implementing the above-described method according to an embodiment of the present disclosure is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto.

[0132] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0133] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. This propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium.

[0134] Program code for performing the operations disclosed herein can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing devices can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN).

[0135] Exemplary device

[0136] Having introduced the medium of exemplary embodiments of this disclosure, the following references are made to... Figure 6 The supply chain strategy determination apparatus of the exemplary embodiments of this disclosure will be described, which is used to implement the supply chain strategy determination method in any of the above method embodiments. Its implementation principle and technical effect are similar, and will not be repeated here.

[0137] The supply chain strategy determination apparatus 600 provided in this disclosure includes:

[0138] The simulation module 610 is used to input key supply chain data and preset strategy parameter groups into the simulation model of the target strategy type based on the target strategy type, and output inventory characteristic data. The key supply chain data includes historical supply chain indicator data, current inventory data and predicted sales data. The strategy parameter group is used to represent the strategy parameters corresponding to the set links of the supply chain.

[0139] Evaluation module 620 is used to calculate corresponding evaluation indicators based on predicted inventory characteristic data;

[0140] The output module 630 is used to determine whether the evaluation indicators meet the preset values ​​and to determine the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type.

[0141] In one exemplary embodiment of this disclosure, the simulation module 610 includes: historical supply chain indicator data including at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data, and historical stockout rate corresponding to various types of goods; current inventory data including at least one of the following: current inventory product type, quantity, seasonal attributes, and inventory classification; and predicted sales data including at least one of the following: predicted sales of various types of goods, predicted activity sales, and predicted activity data.

[0142] In one exemplary embodiment of this disclosure, the simulation module 610 includes: a strategy parameter group including at least one of the following: the replenishment frequency and procurement cycle corresponding to the warehouse, the minimum order quantity corresponding to the supplier, and the safety stock days corresponding to the product.

[0143] In an exemplary embodiment of this disclosure, the output module 630 is specifically configured to: when the target strategy type includes a replenishment strategy, an arrival strategy, and an inventory balancing strategy; if the target strategy type is a replenishment strategy, calculate the replenishment quantity corresponding to the warehouse at each time node based on a preset strategy parameter set and inventory characteristic data; if the target strategy type is an arrival strategy, calculate the time node, replenishment time, and corresponding warehouse at which the supplier should replenish goods based on the preset strategy parameter set and inventory characteristic data; if the target strategy type is an inventory balancing strategy, determine the inventory quantity corresponding to each warehouse at each time node based on the preset strategy parameter set and inventory characteristic data.

[0144] In one exemplary embodiment of this disclosure, the simulation module 610 is specifically configured to: input key supply chain data and a preset set of strategy parameters into a simulation model of the target strategy type based on the target strategy type to obtain a strategy output for a unit time; input the strategy output into the simulation model of the target strategy type to obtain a strategy output for the next unit time; repeat the step of obtaining the strategy output for the next unit time until the total time corresponding to the strategy output is the set cycle length, and use the strategy output as predicted inventory characteristic data.

[0145] In one exemplary embodiment of this disclosure, the evaluation module 620 is specifically used for: inventory characteristic data including inventory data and sales data; and calculating the stockout rate for each product in each warehouse based on the inventory data and sales data.

[0146] In one exemplary embodiment of this disclosure, the output module 630 is specifically configured to: calculate the corresponding evaluation index based on the predicted inventory characteristic data; if the evaluation index does not meet the preset value, reset the strategy parameter group and input it together with the key supply chain data into the simulation model of the target strategy type to obtain the corresponding inventory characteristic data; determine the evaluation index corresponding to the inventory characteristic data; repeat the steps of resetting the strategy parameter group until the corresponding evaluation index is calculated until the set conditions are met; and determine the supply chain strategy based on the strategy parameter group, inventory characteristic data and target strategy type corresponding to the set conditions being met.

[0147] In one exemplary embodiment of this disclosure, the output module 630 includes: setting conditions including at least one of the following: the number of times the strategy parameter group is repeatedly set reaches a set number; the index corresponding to the strategy parameter group meets a preset value.

[0148] Exemplary computing device

[0149] Having described the methods, media, and apparatus of exemplary embodiments of this disclosure, the following references... Figure 7 A computing device according to an exemplary embodiment of the present disclosure will be described.

[0150] Figure 7 The computing device 70 shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0151] like Figure 7 As shown, the computing device 70 is presented in the form of a general-purpose computing device. The components of the computing device 70 may include, but are not limited to: at least one processing unit 701, at least one storage unit 702, and a bus 703 connecting different system components (including the processing unit 701 and the storage unit 702).

[0152] The 703 bus includes a data bus, a control bus, and an address bus.

[0153] Storage unit 702 may include readable media in the form of volatile memory, such as random access memory (RAM) 7021 and / or cache memory 7022, and may further include readable media in the form of non-volatile memory, such as read-only memory (ROM) 7023.

[0154] Storage unit 702 may also include a program / utility 7025 having a set (at least one) program module 7024, such program module 7024 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0155] The computing device 70 can also communicate with one or more external devices 704 (e.g., keyboard, pointing device, etc.). This communication can be performed via the input / output (I / O) interface 705. Furthermore, the computing device 70 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via a network adapter 706. Figure 7 As shown, network adapter 706 communicates with other modules of computing device 70 via bus 703. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with computing device 70, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0156] It should be noted that although several units / modules or sub-units / modules of the supply chain strategy determination device and the object scoring model training device are mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0157] Furthermore, although the operations of the methods disclosed herein are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0158] While the spirit and principles of this disclosure have been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for convenience of expression. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A supply chain strategy determination method characterized by, The method comprises: based on the target strategy type, inputting supply chain key data and a preset strategy parameter group into a simulation model of the target strategy type, outputting inventory characteristic data, the supply chain key data comprising historical supply chain index data, current inventory data and predicted sales data, the strategy parameter group being used to represent strategy parameters corresponding to set links of a supply chain; based on the inventory characteristic data, calculating corresponding evaluation indexes, the evaluation indexes comprising out-of-stock rate, inventory fluctuation rate and / or inventory turnover rate of a commodity; determining a supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type when the evaluation indexes meet preset values, the strategy parameter group comprising at least one of replenishment frequency and procurement cycle of a warehouse, minimum order quantity of a supplier and safety stock days of a commodity, and the inventory characteristic data comprising inventory data and sales data; the historical supply chain index data comprising historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data and historical out-of-stock rate of each type of commodity; the current inventory data comprising type, quantity, seasonal attribute and inventory classification of a current inventory commodity; the predicted sales data comprising predicted sales, predicted activity sales and predicted activity data of each type of commodity; the inputting of the supply chain key data and the preset strategy parameter group into the simulation model of the target strategy type based on the target strategy type to output predicted inventory characteristic data comprises: inputting the supply chain key data and the preset strategy parameter group into the simulation model of the target strategy type based on the target strategy type to obtain strategy output of a unit time length; inputting the strategy output, the preset strategy parameter group, the historical supply chain index data and the predicted sales data into the simulation model of the target strategy type to obtain strategy output of a next unit time length; repeating the step of obtaining strategy output of a next unit time length until the total time length corresponding to the strategy output is a set cycle length, and taking the finally output result as predicted inventory characteristic data.

2. The supply chain strategy determination method according to claim 1, wherein the target strategy type comprises replenishment strategy, arrival strategy and inventory balancing strategy; the determination of the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type comprises: if the target strategy type is replenishment strategy, calculating replenishment quantity of a warehouse at each time node based on the preset strategy parameter group and inventory characteristic data; if the target strategy type is arrival strategy, calculating time node, replenishment time and corresponding warehouse of a supplier that should be replenished based on the preset strategy parameter group and inventory characteristic data; if the target strategy type is inventory balancing strategy, determining inventory quantity of each warehouse at each time node based on the preset strategy parameter group and inventory characteristic data.

3. The supply chain strategy determination method according to claim 1 or 2, wherein the calculation of the corresponding evaluation indexes based on the inventory characteristic data comprises: ​ Based on the inventory data and the sales data, a stock-out rate corresponding to each commodity in each warehouse is calculated.

4. The supply chain strategy determination method according to claim 1 or 2, after the step of calculating the evaluation index corresponding to the inventory characteristic data, the method further comprises: if the evaluation index does not meet the preset value, resetting the strategy parameter set and inputting the supply chain key data into the simulation model of the target strategy type to obtain corresponding inventory characteristic data; determining the evaluation index corresponding to the inventory characteristic data; repeating the step of resetting the strategy parameter set until the set condition is met; determining the supply chain strategy based on the strategy parameter set, the inventory characteristic data and the target strategy type when the set condition is met.

5. The supply chain strategy determination method according to claim 4, the set condition comprises at least one of the following: the number of times of resetting the strategy parameter set reaches the set number of times; the index corresponding to the strategy parameter set meets the preset value.

6. A computer-readable storage medium comprising: The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the supply chain strategy determination method according to any one of claims 1 to 5.

7. A supply chain strategy determination device, the device comprising: a simulation module, configured to input supply chain key data and a preset strategy parameter set into a simulation model of a target strategy type based on the target strategy type, output inventory characteristic data, the supply chain key data comprising historical supply chain index data, current inventory data and predicted sales data, and the strategy parameter set being used to represent strategy parameters corresponding to set links of a supply chain; an evaluation module, configured to calculate an evaluation index based on the inventory characteristic data, the evaluation index comprising a stock-out rate of a commodity, an inventory fluctuation rate and / or an inventory turnover rate; an output module, configured to determine that the evaluation index meets a preset value, and determine a supply chain strategy based on the preset strategy parameter set, the inventory characteristic data and the target strategy type, the strategy parameter set comprising at least one of the following: a replenishment frequency and a procurement cycle corresponding to a warehouse, a minimum order quantity corresponding to a supplier, and a safety stock period corresponding to a commodity; the inventory characteristic data comprises inventory data and sales data; the historical supply chain index data comprises historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data and historical stock-out rate corresponding to each type of commodity; the current inventory data comprises a type, a quantity, a seasonal attribute and an inventory classification of a current inventory commodity; the predicted sales data comprises predicted sales, predicted activity sales and predicted activity data of each type of commodity; the simulation module is specifically configured to: input the supply chain key data and the preset strategy parameter set into the simulation model of the target strategy type based on the target strategy type to obtain a strategy output of a unit time period; input the strategy output, the preset strategy parameter set, the historical supply chain index data and the predicted sales data into the simulation model of the target strategy type to obtain a strategy output of a next unit time period; and determine the supply chain strategy based on the strategy parameter set, the inventory characteristic data and the target strategy type when the set condition is met. The step of obtaining the policy output of the next unit length is repeated until the total length of the policy output corresponds to the set period length, and the last output result is taken as the predicted inventory feature data. 8.The supply chain strategy determination apparatus of claim 7, wherein the output module is specifically configured to: when the target strategy type comprises a replenishment strategy, a delivery strategy, or an inventory balancing strategy, if the target strategy type is the replenishment strategy, based on the preset strategy parameter group and the inventory feature data, the replenishment amount of each warehouse at each time node is calculated; if the target strategy type is the delivery strategy, based on the preset strategy parameter group and the inventory feature data, the time node at which the supplier should replenish, the replenishment time, and the corresponding warehouse are calculated; if the target strategy type is the inventory balancing strategy, based on the preset strategy parameter group and the inventory feature data, the inventory amount of each warehouse at each time node is determined. 9.The supply chain strategy determination apparatus of claim 7 or 8, wherein the evaluation module is specifically configured to: based on the inventory data and the sales data, the out-of-stock rate of each commodity in each warehouse is calculated. 10.The supply chain strategy determination apparatus of claim 7 or 8, wherein the output module is specifically configured to: after the corresponding evaluation index is calculated based on the inventory feature data, if the evaluation index does not meet the preset value, the strategy parameter group is reset, and the supply chain key data is input into the simulation model of the target strategy type to obtain the corresponding inventory feature data; the evaluation index corresponding to the inventory feature data is determined; the step of resetting the strategy parameter group is repeated until the step of calculating the corresponding evaluation index is met until the set condition is met; based on the strategy parameter group, the inventory feature data, and the target strategy type corresponding to the set condition, the supply chain strategy is determined. 11.The supply chain strategy determination apparatus of claim 10, wherein the output module comprises: the set condition comprises at least one of the following: the number of times of resetting the strategy parameter group reaches the set number of times; the index corresponding to the strategy parameter group meets the preset value.

12. A computing device comprising: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to cause the computing device to perform the supply chain strategy determination method of any one of claims 1 to 5.

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