CN115375149A - Supply chain strategy determination method, medium, device and computing device - Google Patents

Abstract

The embodiment of the disclosure provides a supply chain strategy determination method, medium, device and computing equipment. The method comprises the following steps: inputting the supply chain key data and a preset strategy parameter group into a simulation model of the target strategy type based on the target strategy type, and outputting inventory characteristic data; calculating a corresponding evaluation index based on the predicted inventory characteristic data; and determining that the evaluation index meets a preset value, and determining a supply chain strategy based on a preset strategy parameter group, inventory characteristic data and a target strategy type. The method solves the problem that the reliability of the supply chain strategy is insufficient due to the fact that the supply chain strategy of the whole link cannot be calculated in a unified mode in the related technology, and remarkably improves the formulation efficiency and reliability of the supply chain strategy.

Description

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

technical field

Embodiments of the present disclosure relate to the technical field of supply chain inventory management, and more specifically, embodiments of the present disclosure relate to a method, medium, device, and computing device for determining a supply chain strategy.

Background technique

This section is intended to provide a background or context for implementations of the disclosure that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section.

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

In e-commerce logistics distribution, the whole supply chain process is that upstream suppliers set up direct stores or brand retail stores on e-commerce platforms, consumers place orders on e-commerce platforms, and e-commerce platforms send orders to third-party logistics companies , stored and transported by third-party logistics companies. The process of product circulation is that the products produced by the upstream supplier's production workshop enter the warehouses of the third-party logistics company in advance, and the third-party logistics company then ships the products out of the warehouse to consumers according to the order.

Among them, strategies such as when the warehouse initiates an order to the supplier and how many different types of goods should be stored have the greatest impact on the overall performance of the entire supply chain link. very important.

However, the supply chain strategy of the full link is affected by various factors such as demand uncertainty, logistics uncertainty, supplier uncertainty, and inventory cycle, and the time period is long and the amount of calculation is huge. The unified calculation of the strategy makes it difficult to control the overall performance of the supply chain in the entire region.

Contents of the invention

The present disclosure provides a supply chain strategy determination method, medium, device and computing equipment to solve the problem in the related art that the supply chain strategy of the whole link cannot be calculated uniformly, resulting in insufficient reliability of the supply chain strategy.

In the first aspect of the embodiments of the present disclosure, a method for determining a supply chain strategy is provided, including:

Based on the target strategy type, input the key data of the supply chain and the preset strategy parameter group into the simulation model of the target strategy type, and output the inventory characteristic data. The key data of the supply chain include historical supply chain index data, current inventory data and forecast sales data , the strategy parameter group is used to represent the strategy parameters corresponding to the setting link of the supply chain;

Based on the predicted inventory characteristic data, calculate the corresponding evaluation index;

Determine that the evaluation index satisfies the preset value, and determine the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type.

In one embodiment of the present disclosure, the 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 stock-out rate corresponding to various types of commodities; current inventory The data includes at least one of the following: type, quantity, seasonal attribute, and inventory classification of current inventory commodities; the forecasted sales data includes at least one of the following: forecasted sales of various types of goods, forecasted activity sales, and forecasted activity data.

In an exemplary embodiment of the present disclosure, the policy parameter group includes at least one of the following: replenishment frequency and procurement cycle corresponding to the warehouse, minimum order quantity corresponding to the supplier, and safety stock days corresponding to the commodity.

In an exemplary embodiment of the present disclosure, the target strategy type includes a replenishment strategy, an arrival strategy, and an inventory balance strategy; determining a supply chain strategy based on a preset strategy parameter group, inventory characteristic data, and the target strategy type includes: If the target strategy type is a replenishment strategy, calculate the replenishment quantity corresponding to the warehouse at each time node based on the preset strategy parameter group and inventory feature data; if the target strategy type is an arrival strategy, based on the preset strategy parameter group and inventory feature data, calculate the time node when the supplier should replenish, the replenishment time and the corresponding warehouse; if the target strategy type is an inventory balance strategy, based on the preset strategy parameter group and inventory feature data, determine each time node The inventory corresponding to the warehouse.

In an exemplary embodiment of the present disclosure, based on the target strategy type, the key data of the supply chain and the preset strategy parameter group are input into the simulation model of the target strategy type, and the predicted inventory characteristic data is output, including: For the strategy type, input the key data of the supply chain and the preset strategy parameter group into the simulation model of the target strategy type to obtain the strategy output per unit duration; input the strategy output into the simulation model of the target strategy type to obtain the next unit duration strategy output; repeat the step of obtaining the strategy output of the next unit duration until the total duration corresponding to the strategy output is the set cycle length, and use the strategy output as the predicted inventory feature data.

In an exemplary embodiment of the present disclosure, the inventory feature data includes inventory data and sales data; calculating the corresponding evaluation index based on the inventory feature data includes: calculating the corresponding value of each commodity in each warehouse based on the inventory data and sales data out-of-stock rate.

In an exemplary embodiment of the present disclosure, after calculating the corresponding evaluation index based on the inventory feature data, the method further includes: if the evaluation index does not meet the preset value, resetting the policy parameter group, and The key data of the supply chain are jointly input into the simulation model of the target strategy type to obtain the corresponding inventory feature data; determine the corresponding evaluation index of the inventory feature data; repeat the steps of resetting the strategy parameter group to calculate the corresponding evaluation index, until Satisfy the set conditions; determine the supply chain strategy based on the corresponding strategy parameter group, inventory characteristic data and target strategy type when the set conditions are met.

In an exemplary embodiment of the present disclosure, the setting condition includes at least one of the following: the number of times the policy parameter group is repeatedly set reaches the set number of times; the index corresponding to the policy parameter group satisfies a preset value.

In a second aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, including:

The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to implement the supply chain strategy determination method in the first aspect of the present disclosure when executed by the processor.

In a third aspect of the present disclosure, an apparatus for determining a supply chain strategy is provided, including:

The simulation module is used to input the key data of the supply chain and the preset strategy parameter group into the simulation model of the target strategy type based on the target strategy type, and output the inventory characteristic data. The key data of the supply chain include historical supply chain index data, current inventory Data and forecasted sales data, the strategy parameter group is used to represent the strategy parameters corresponding to the setting link of the supply chain;

An evaluation module, configured to calculate corresponding evaluation indicators based on the predicted inventory characteristic data;

The output module is used to determine that the evaluation index satisfies the preset value, and determine the supply chain strategy based on the preset strategy parameter group, inventory feature data and target strategy type.

In an exemplary embodiment of the present disclosure, the simulation module includes: the historical supply chain index data includes at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, historical inventory fluctuation data and Historical out-of-stock rate; current inventory data includes at least one of the following: current inventory product type, quantity, seasonal attributes, and inventory classification; forecasted sales data includes at least one of the following: forecasted sales of various types of goods, forecasted activity sales, and forecasted activities data.

In an exemplary embodiment of the present disclosure, the simulation module includes: the policy parameter group includes at least one of the following: replenishment frequency and procurement cycle corresponding to the warehouse, minimum order quantity corresponding to the supplier, and safety stock days corresponding to the product .

In an exemplary embodiment of the present disclosure, the output module is specifically configured to: when the target strategy type includes a replenishment strategy, an arrival strategy, and an inventory balance strategy, if the target strategy type is a replenishment strategy, based on a preset strategy Parameter group and inventory characteristic data, calculate the replenishment quantity corresponding to the warehouse at each time node; if the target strategy type is arrival strategy, based on the preset strategy parameter group and inventory characteristic data, calculate the time node that the supplier should replenish , replenishment time and corresponding warehouse; if the target strategy type is inventory balance strategy, based on the preset strategy parameter group and inventory characteristic data, determine the inventory corresponding to each warehouse at each time node.

In an exemplary embodiment of the present disclosure, the simulation module is specifically used to: based on the target strategy type, input the key data of the supply chain and the preset strategy parameter group into the simulation model of the target strategy type to obtain the strategy of the unit duration Output; input the strategy output into the simulation model of the target strategy type to obtain the strategy output of the next unit duration; repeat the step of obtaining the strategy output of the next unit duration until the total duration corresponding to the strategy output is the set cycle length, Use policy output as predicted inventory feature data.

In an exemplary embodiment of the present disclosure, the evaluation module is specifically configured to: the inventory feature data includes inventory data and sales data; based on the inventory data and sales data, calculate the out-of-stock rate corresponding to each commodity in each warehouse.

In an exemplary embodiment of the present disclosure, the output module is specifically configured to: after calculating 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 communicate with the supply The chain key data are jointly input into the simulation model of the target strategy type to obtain the corresponding inventory characteristic data; determine the corresponding evaluation index of the inventory characteristic data; repeat the steps of resetting the strategy parameter group to calculate the corresponding evaluation index, until the set conditions are met; The supply chain strategy is determined based on the corresponding strategy parameter group, inventory feature data and target strategy type when the set conditions are met.

In an exemplary embodiment of the present disclosure, the output module includes: the setting condition includes at least one of the following: the number of times the strategy parameter group is repeatedly set reaches the set number of times; the index corresponding to the strategy parameter group satisfies a preset value.

In a fourth aspect of the embodiments of the present disclosure, a computing device is provided, including: at least one processor;

and a memory communicatively connected to at least one processor;

Wherein, the memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor, so that the computing device executes the supply chain strategy determination method in the first aspect of the present disclosure.

According to the supply chain strategy determination method, medium, device and computing device of the embodiments of the present disclosure, based on the target strategy type, the key data of the supply chain and the preset strategy parameter group are input into the simulation model of the target strategy type, and the inventory characteristics are output Based on the predicted inventory feature data, calculate the corresponding evaluation index to determine that the evaluation index meets the preset value, and determine the supply chain strategy based on the preset strategy parameter group, inventory feature data, and target strategy type. As a result, the historical index data, current inventory data, and forecasted sales data of the entire supply chain are used as input data for analysis, so as to realize the unified calculation of the decision-making of the whole link, rather than limited to the calculation of a certain module, to achieve a single The model calculates the full link strategy of the complex supply chain, which significantly improves the calculation efficiency. And by combining with the preset strategy parameter group, the strategy can be adjusted according to the demand, and then the optimal supply chain strategy can be obtained, thereby ensuring the optimization of the overall efficiency of the supply chain.

Description of drawings

The above and other objects, features and advantages of exemplary embodiments of the present disclosure will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the present disclosure are shown by way of illustration and not limitation, in which:

FIG. 1 schematically shows an application scenario diagram according to an embodiment of the present disclosure;

Fig. 2 schematically shows a flow chart of a method for determining a supply chain strategy according to another embodiment of the present disclosure;

Fig. 3 schematically shows a flowchart of a method for determining a supply chain strategy according to yet another embodiment of the present disclosure;

Fig. 4 schematically shows a flowchart of a method for determining a supply chain strategy according to yet another embodiment of the present disclosure;

Fig. 5 schematically shows a schematic structural diagram of a storage medium according to yet another embodiment of the present disclosure;

Fig. 6 schematically shows a schematic structural view of an apparatus for determining a supply chain strategy according to yet another embodiment of the present disclosure;

Fig. 7 schematically shows a schematic structural diagram of a computing device according to yet another embodiment of the present disclosure.

In the drawings, the same or corresponding reference numerals denote the same or corresponding parts.

Detailed ways

The principle and spirit of the present disclosure will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present disclosure, rather than to limit the scope of the present disclosure in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Those skilled in the art know that the embodiments of the present disclosure may be implemented as a system, device, device, method or computer program product. Therefore, the present disclosure may be embodied in the form of complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

According to the embodiments of the present disclosure, a supply chain strategy determination method, medium, device and computing device are proposed.

In this article, it should be understood that the terms involved are only used to facilitate understanding, and do not represent limitations on meanings. In addition, any number of elements in the drawings is used for illustration rather than limitation, and any designation is only for distinction and does not have any limiting meaning.

The following is a description of terms involved in this disclosure:

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

Target strategy type: Starting from different links, there will be different goals for the supply chain strategy, which is the target strategy type. For example, the target strategy type corresponding to the warehouse should reduce the storage time of the goods under the premise of ensuring a complete range of goods, while the target strategy type corresponding to the supplier only needs to consider the delivery time or quantity, and does not need to consider the storage situation of the goods in the warehouse.

The principle and spirit of the present disclosure will be explained in detail below with reference to several representative embodiments of the present disclosure.

Summary of the invention

The inventors found that in the current technology, logistics and distribution fields such as e-commerce rely heavily on the performance of the supply chain with warehouses as the core. When the efficiency of the supply chain is high, the goods sent by the supplier can reach the warehouse in time and in sufficient quantity, and be sent to the corresponding consumers in time, and the storage time of the goods in the warehouse is short. Conversely, when the efficiency of the supply chain is low, the warehouse cannot timely Or replenish the goods in sufficient quantity, and cannot send the goods to consumers in time, and at the same time, the goods stay in the warehouse for too long. Therefore, it is of great significance to optimize the efficiency of the supply chain by determining the appropriate supply chain strategy for the logistics and distribution fields such as e-commerce.

Since the whole link of the supply chain includes multiple links from supplier supply, warehouse receipt to external delivery, and each link has different strategy parameters, the existing technology usually models each link separately. In order to determine the supply chain strategy of each link, the strategy parameters of each link are relatively independent, and the calculation cycle is long. When there is an error in a certain link, the overall error will be rapidly amplified due to the existence of multiple links, resulting in serious reliability. restricted.

In this scheme, the key data of the supply chain of the whole link are included in the calculation, and the strategy parameter group including each link of the whole link is used for evaluation, and then the supply chain strategy of the whole link is determined, with high efficiency and small error , strong reliability.

After introducing the basic principles of the present disclosure, various non-limiting embodiments of the present disclosure are described in detail below.

Overview of application scenarios

First, as shown in FIG. 1 , in the supply chain, the warehouse 100 determines the frequency and quantity of goods obtained from the supplier 110 based on the supply chain strategy, and determines the quantity and duration of the goods stored in the warehouse 100, and the delivery of the goods to the retailer 120 or The speed and quantity of delivery by the user 130, so as to complete the logistics distribution process of the supply chain.

It should be noted that the warehouse, supplier, goods, retailer, and user in the scenario shown in Figure 1 are only illustrated as an example, but the present disclosure is not limited thereto, that is to say, warehouses, suppliers, goods , the number of retailers and users can be arbitrary.

exemplary method

The method for determining a supply chain strategy according to an exemplary embodiment of the present disclosure will be described below with reference to FIGS. 2 to 4 in conjunction with the application scenario of FIG. 1 . It should be noted that the above-mentioned application scenarios are only shown to facilitate understanding of the spirit and principle of the present disclosure, and implementations of the present disclosure are not limited in this respect. On the contrary, the embodiments of the present disclosure can be applied to any applicable scene.

Fig. 2 is a flowchart of a method for determining a supply chain strategy provided by an embodiment of the present disclosure. As shown in Figure 2, the supply chain strategy determination method provided in this embodiment includes the following steps:

Step S201 , based on the target strategy type, input supply chain key data and a preset strategy parameter group into the simulation model of the target strategy type, and output inventory feature data.

Among them, the key data of the supply chain includes historical supply chain index data, current inventory data and forecasted sales data, and the strategy parameter group is used to represent the strategy parameters corresponding to the setting links of the supply chain.

Specifically, due to the different factors and goals that need to be considered in the selection of target strategy types from the perspective of different links, for example, from the perspective of retailers or users, it is not necessary to consider the frequency of supplier shipments, and from the perspective of suppliers, it is not necessary to consider The storage time of the goods in the warehouse, therefore, the model parameters of the simulation model corresponding to different target strategy types will be different. In actual use, it is first necessary to determine the target strategy to be analyzed, so that based on the simulation model of the target strategy type, a corresponding preset strategy parameter group is selected for calculation.

The preset strategy parameter group is the strategy parameter of each link preliminarily determined based on the key data of the supply chain. By substituting the preset strategy parameter group and the key data of the supply chain into the simulation model for calculation, the calculated results can be evaluated Whether the preset policy parameter set is feasible, if not, adjust the preset policy parameter set based on the evaluation results, and then substitute it into the simulation model for calculation until the adjusted policy parameter set passes the evaluation.

The strategy parameters corresponding to each link in the preset strategy parameter group can be determined based on the historical strategy parameter group and the key data of the supply chain. If the monthly sales volume is average, the replenishment frequency in the strategic parameters corresponding to the first quarter of this kind of goods can be preset as once a month, and the minimum replenishment quantity is preset as 1000 copies; or according to the current inventory data, the stock of this kind of goods is kept at 1800 copies, the preset replenishment frequency can be set to once every 1.5 months, and the minimum replenishment quantity is preset to 600 copies each time.

The setting links can have different components according to different division methods, but usually include at least three links: suppliers (suppliers), warehouses, and consumers. The warehouse link can also be replaced by a distribution enterprise. Retailers can be included, and manufacturers (manufacturers) can also be included between suppliers and warehouses. Each link has different strategy parameters, so it needs to be discussed separately.

The inventory feature data corresponds to the current inventory data, which means the inventory data output by the simulation model after the end of the current cycle, including the quantity of various goods stored in the warehouse, storage time and other index data, and can also include inventory fluctuations, out-of-stock probabilities, etc. High-level index data (can be calculated through changes in the quantity of goods stored and sales).

Step S202, calculating corresponding evaluation indicators based on the inventory feature data.

Specifically, after determining the simulation model of the target strategy type, key supply chain data and preset strategy parameter groups are input into the simulation model, and corresponding inventory feature data will be output. Since the supply chain duration that needs to be calculated in practical applications usually involves multiple cycles (for example, the total duration is a whole year, each month can be regarded as a cycle at this time), therefore, after obtaining the inventory characteristic data after the end of the current cycle Finally, if the period that needs to be calculated also includes uncalculated cycles, the inventory feature data, historical supply chain index data, and forecasted sales data will be used together as the new supply chain key data, combined with the preset strategy parameter group, and again It is substituted into the simulation model, and the calculation of the next cycle is performed until all cycles are completed, and the final output result is used as the final inventory characteristic data.

Based on the finally obtained inventory characteristic data, its corresponding evaluation index can be calculated, such as the average storage time of a certain kind of goods (or the average storage time of all goods corresponding to the warehouse link), to judge whether it meets the requirements.

Step S203, determining that the evaluation index satisfies the preset value, and determining the supply chain strategy based on the preset strategy parameter group, inventory feature data and target strategy type.

Specifically, each evaluation index has a preset threshold (that is, a preset value). If the evaluation index meets the preset value (for example, the calculated goods inventory fluctuation index is 0.5, which is less than the preset value of 0.6, it is considered to meet the preset threshold). value), that is, it can be considered that the preset strategy parameter group can meet the requirements of the target strategy type, and then the supply chain strategy corresponding to the target strategy type can be determined based on the strategy parameter group. For example, when the target strategy type is a replenishment strategy, based on the strategy The replenishment frequency parameter value in the parameter group is 100 pieces/week, and the corresponding supply chain strategy is determined to apply to the supplier for replenishment of 100 pieces per week.

If the evaluation index does not meet the preset value, it is necessary to readjust the preset strategy parameter group, and then substitute it into step S201 to step S202, and recalculate. For example, the calculated goods inventory fluctuation index is 0.9, which is greater than the preset value of 0.6 , that is, it is considered that the preset value is not satisfied. At this time, the replenishment frequency in the preset strategy parameter group can be shortened, and then recalculated.

According to the supply chain strategy determination method of the embodiment of the present disclosure, based on the target strategy type, the key data of the supply chain and the preset strategy parameter group are input into the simulation model of the target strategy type, and the inventory characteristic data is output, and then based on the predicted inventory Characteristic data, calculate the corresponding evaluation index, to determine that the evaluation index meets the preset value, and determine the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type. As a result, the historical index data, current inventory data, and forecasted sales data of the entire supply chain are used as input data for analysis, so as to realize the unified calculation of the decision-making of the whole link, rather than limited to the calculation of a certain module, to achieve a single The model calculates the full link strategy of the complex supply chain, which significantly improves the calculation efficiency. And by combining with the preset strategy parameter group, the strategy can be adjusted according to the demand, and then the optimal supply chain strategy can be obtained, thereby ensuring the optimization of the overall efficiency of the supply chain.

Fig. 3 is a flowchart of a method for determining a supply chain strategy provided by an embodiment of the present disclosure. As shown in Figure 3, the supply chain strategy determination method provided in this embodiment includes the following steps:

Step S301 , based on the target strategy type, input the supply chain key data and the preset strategy parameter group into the simulation model of the target strategy type to obtain the strategy output per unit duration.

Among them, the key data of the supply chain includes historical supply chain index data, current inventory data and forecasted sales data, and the strategy parameter group is used to represent the strategy parameters corresponding to the setting links of the supply chain.

Specifically, the unit duration is a part of the total duration of the supply chain to be calculated, and different unit durations can be selected according to different situations. If the calculation object is the warehouse inventory balance strategy in the peak season (such as shopping festival activities), the flow of goods is faster at this time, and the unit duration can be 24 hours or three days (for example, when shipping in the same city, the warehouse to the consumer can be completed within 24 hours. The flow from the supplier to the warehouse; in the case of regular delivery, the flow between each link can be completed within 72 hours), after each unit of time, the corresponding inventory data is determined based on the strategy parameter group and the key data of the supply chain.

Since the inventory data obtained at this time is not the final output inventory feature data, it is named strategy output, which corresponds to the target strategy type. If the target strategy type is the retailer's or consumer's arrival strategy, the strategy output can be the ordering strategy output; the target strategy type is the supplier's replenishment strategy, and the strategy output can be the transportation strategy output; the target strategy type is the inventory balance of the warehouse strategy, the strategy output is the storage capacity strategy output.

Further, the 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 stock-out rates corresponding to various types of commodities; current inventory data includes at least one of the following : The type, quantity, season attribute, and inventory classification of the current inventory commodity; the forecasted sales data includes at least one of the following: forecasted sales volume of various types of goods, forecasted activity sales volume, and forecasted activity data.

Specifically, the types of current inventory items include their physical types (such as large items, fragile items) and sales types (such as cosmetics, electronic items), and the seasonal attribute is used to represent the sales distribution of items in different seasons. For example, Christmas trees are usually only sold in The sales volume in the fourth quarter was high, and the sales volume in the other three quarters was extremely low; the inventory classification is used to indicate the storable nature of the product, such as whether it is an item that is not resistant to storage such as fresh food, whether it can be stored in large quantities (such as a product that needs to be customized) , it cannot be stored in large quantities), etc.; forecasted sales include expected sales (such as the expected sales of an audio-visual product to reach 200,000 copies) and possible sales based on historical data (such as a shampoo that can directly use the sales of this quarter as the next Quarterly possible sales volume), forecast event sales volume is used to represent the sales volume in expected activities (such as shopping festival activities), and the forecast activity data includes possible activities and business models (such as single-order mode or group-buying mode).

In an embodiment of the solution, the policy parameter group includes at least one of the following: replenishment frequency and procurement cycle corresponding to the warehouse, minimum order quantity corresponding to the supplier, and safety stock days corresponding to the commodity.

Specifically, the replenishment frequency and procurement cycle corresponding to the warehouse have a greater impact on inventory fluctuations, the minimum order quantity corresponding to the supplier has a greater impact on the delivery frequency, and the number of days of product safety stock (it can be the shelf life or the expected storage period) Time, such as frozen items, although the actual storage time is longer, the expected storage time is usually shorter, because the value will decrease after long-term storage).

Step S302, inputting the policy output into the simulation model of the target policy type to obtain the policy output of the next unit duration.

Specifically, the strategy output is used together with the preset strategy parameter group, historical supply chain index data, and forecasted sales data as input data in the next unit duration, and is input into the simulation model to obtain the strategy output of the next market.

Step S303 , repeating the step of obtaining the strategy output of the next unit duration until the total duration corresponding to the strategy output is the set cycle length, and using the strategy output as the predicted inventory feature data.

Specifically, after the cycle of all the total duration is completed, the finally obtained strategy is output as the final output inventory feature data.

In an embodiment of this solution, the inventory feature data includes inventory data and sales data.

Specifically, the inventory feature data includes inventory data such as inventory quantity and inventory fluctuation of each commodity in the warehouse, and sales data of each commodity.

Step S304, based on the inventory data and sales data, calculate the out-of-stock rate corresponding to each product in each warehouse.

Specifically, among the evaluation indicators, the most important thing is the out-of-stock rate of the product, because the out-of-stock rate of the product has the greatest impact on the supply chain. Therefore, the out-of-stock rate of each product can be calculated based on the inventory data and sales data.

In one embodiment of this solution, in addition to the out-of-stock rate, it also includes the inventory volatility and/or inventory turnover rate of the commodity, because when the inventory volatility is large, the commodity is likely to be out of stock, and the supply chain strategy also needs to be improved; and When the inventory turnover rate (used to evaluate the turnover time of goods in the warehouse stage) is large, it is easy to cause goods to stay in the warehouse for a long time, and the supply chain strategy also needs to be improved.

Step S305, if the target strategy type is a replenishment strategy, calculate the replenishment quantity corresponding to the warehouse at each time node based on the preset strategy parameter group and inventory feature data.

Specifically, depending on the type of the target strategy, the specific data of the supply chain strategy to be determined is also different. For the replenishment strategy, the most important data is the replenishment quantity at each time node.

The time node can be the unit duration in the aforementioned calculation, or it can be a unit smaller or larger than the unit duration, for example, the unit duration is every 72 hours, and the time node can be 24 hours, 72 hours or every week, because The time for the warehouse to ship goods to the outside world is uncertain, so the time for applying for replenishment can be very short (such as when the shipment volume and frequency are large) or very long (such as the off-season).

The amount of replenishment can be calculated from the replenishment frequency and procurement cycle in the strategy parameter group, as well as the current inventory quantity and forecasted sales volume in the key data of the supply chain.

In an embodiment of this solution, the replenishment strategy includes replenishment frequency in addition to replenishment quantity. When the delivery volume and time of the product are not fixed (such as products limited to specific festivals), the specific replenishment frequency will also be determined, such as moon cakes. During the period of three months to one month from the Mid-Autumn Festival, the replenishment frequency It can be once a week. From one month before the Mid-Autumn Festival to the day of the Mid-Autumn Festival, the replenishment frequency can be once every two weeks (because most people will choose to buy in advance), and after the Mid-Autumn Festival, no replenishment is required. Because there is usually no need for replenishment at this time.

Step S306. If the target strategy type is the arrival strategy, calculate the time node when the supplier should replenish the goods, the replenishment time and the corresponding warehouse based on the preset strategy parameter group and inventory characteristic data.

Specifically, the arrival strategy is a target strategy type determined based on the needs of retailers or users. Since retailers and users cannot store goods, the objects that need to be calculated are the supplier's replenishment situation and the warehouse where the replenishment arrives, so that The warehouse can deliver goods in time when it receives the needs of retailers or users. At the same time, because the hands-on or users are more sensitive to time, it is also necessary to determine the replenishment time (such as the goods that need to be temporarily processed by the supplier, it takes several working days to complete the replenishment after receiving the order).

The replenishment time required for each commodity between different suppliers and different warehouses is usually different. Therefore, it is necessary to calculate the corresponding replenishment time, or calculate the average time of the commodity between different suppliers and different warehouses.

Time node and replenishment time, warehouse, you can use the replenishment frequency, procurement cycle, minimum order quantity corresponding to the supplier in the strategy parameter group, as well as the current inventory product season attribute, historical inventory fluctuation data, historical The out-of-stock rate and forecasted sales data are calculated.

Step S307, if the target strategy type is an inventory balance strategy, based on the preset strategy parameter group and inventory characteristic data, determine the corresponding inventory quantity of each warehouse at each time node.

Specifically, the inventory balance strategy is the type of target strategy determined based on the warehouse link. Ideally, for the warehouse, it is necessary to ensure that the inventory fluctuations in the warehouse are not too large, and that each commodity is not out of stock. Therefore, it is necessary to calculate the The inventory corresponding to each warehouse can be used to adjust the replenishment of goods in the warehouse based on the inventory.

Inventory can be calculated from the replenishment frequency in the strategy parameter group, the number of days of safe stock corresponding to the product, and the current inventory quantity, historical inventory data, historical out-of-stock rate, and forecast sales in the key data of the supply chain.

According to the supply chain strategy determination method of the embodiment of the present disclosure, 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 to obtain the strategy output per unit duration, and then the strategy The output is input into the simulation model again, and the cycle is repeated until the end of the entire duration. Based on the output result, the out-of-stock rate of the product is calculated, and the corresponding supply chain strategy is determined according to the type of target strategy. As a result, it is possible to provide a full-link supply chain strategy for complex supply chains, and because there is no need to discuss each link separately, it can handle a large amount of data as an output, improving the reliability and accuracy of the output supply chain strategy.

Fig. 4 is a flowchart of a method for determining a supply chain strategy provided by an embodiment of the present disclosure. As shown in Figure 4, the supply chain strategy determination method provided in this embodiment includes the following steps:

Step S401 , based on the target strategy type, input supply chain key data and a preset strategy parameter group into the simulation model of the target strategy type, and output inventory feature data.

Among them, the key data of the supply chain includes historical supply chain index data, current inventory data and forecasted sales data, and the strategy parameter group is used to represent the strategy parameters corresponding to the setting links of the supply chain.

Step S402, based on the inventory characteristic data, calculate the corresponding evaluation index.

Specifically, steps S401 to S402 are the same as steps S201 to S202 in the embodiment shown in FIG. 2 , and will not be repeated here.

Step S403. If the evaluation index does not meet the preset value, reset the strategy parameter group, and input it together with the supply chain key data into the simulation model of the target strategy type to obtain the corresponding inventory feature data.

Specifically, if the value setting in the strategy parameter group is wrong, resulting in the evaluation index not meeting the preset value (such as a high out-of-stock rate), it is necessary to adjust the value in the strategy parameter group, and then perform steps S401 to S402 again. operation process.

According to the specific situation of numerical errors in the strategy parameter group and the degree of deviation between the evaluation index and the preset value, the strategy parameter group has different adjustment methods. For example, if there is a simple input error, it can be adjusted to the correct value. If the setting is unreasonable, resulting in a high out-of-stock rate, you need to increase the replenishment frequency and other parameters.

In an embodiment of this solution, the adjustment of the policy parameter group can also be manually adjusted according to expert experience, and the policy parameters can be adjusted through the evaluation of relevant personnel.

Step S404, determining the evaluation index corresponding to the inventory feature data.

Specifically, this step is the same as step S402 and the content of step S202 in the embodiment shown in FIG. 2 , and will not be repeated here.

Step S405, repeating the step of resetting the policy parameter group to calculating the corresponding evaluation index until the setting condition is satisfied.

Specifically, if the strategy parameter group obtained after the adjustment sequence still fails to pass the test of the preset value, it is necessary to repeatedly set the strategy parameter group and substitute it into the simulation model for calculation until the corresponding evaluation index is calculated for evaluation.

In one embodiment of this solution, the setting conditions include at least one of the following:

The number of times to repeatedly set the policy parameter group reaches the set number of times;

The indicators corresponding to the policy parameter group meet the preset values.

Specifically, since the strategy parameter group can only play a role in predicting and guiding, it may also occur that the corresponding indicator cannot always meet the preset value (if it is satisfied, just stop and output the result), and the set times will also be adjusted repeatedly After that, the calculation ends. If the set business target (forecast sales or forecast activity sales) is quite different from the historical sales data (for example, the expected sales of a product is too high and exceeds the record), it is very likely that the combination of the setting and the historical supply chain indicators will not be possible. Under certain circumstances, ensure that indicators such as the out-of-stock rate meet the preset values.

Step S406. Determine the supply chain strategy based on the corresponding strategy parameter group, inventory feature data and target strategy type when the set conditions are met.

Specifically, in the case that the policy parameter group satisfies the set conditions, the way to calculate the supply chain policy can refer to step S305 to step S307, which will not be repeated here.

According to the supply chain strategy determination method of the embodiment of the present disclosure, based on the target strategy type, the supply chain key data and the preset strategy parameter group are input into the simulation model of the target strategy type, the inventory characteristic data is output, and based on the inventory characteristic data Calculate the evaluation index. If the evaluation index does not meet the preset value, adjust the preset strategy parameter group and substitute it into the simulation model again for calculation; until the final result is obtained. As a result, the strategy parameter group can be automatically optimized according to the key data of the supply chain and business objectives, and the feasibility and reliability of the supply chain strategy can be improved.

Exemplary medium

After introducing the method of the exemplary embodiment of the present disclosure, next, the storage medium of the exemplary embodiment of the present disclosure will be described with reference to FIG. 7 .

As shown in FIG. 5 , a program product 50 for implementing the above method according to an embodiment of the present disclosure is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program codes, and can be used in terminal equipment, For example running on a personal computer. However, the program product of the present disclosure is not limited thereto.

The program product may reside on any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: electrical connection with one or more conductors, portable disk, 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 of the foregoing.

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

Program code for carrying out the operations disclosed in the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural programming language—such as "C" or a similar programming language. The program code can execute entirely on the user computing device, partly on the user device, partly on the remote computing device, or entirely on the remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN).

Exemplary device

After introducing the medium of the exemplary embodiment of the present disclosure, next, with reference to FIG. 6 , the supply chain policy determination device of the exemplary embodiment of the present disclosure will be described, which is used to implement the supply chain policy determination method in any of the above method embodiments. , its implementation principle and technical effect are similar, and will not be repeated here.

The supply chain strategy determining device 600 provided in the present disclosure includes:

The simulation module 610 is used to input key supply chain data and preset policy parameter groups into the simulation model of the target policy type based on the target policy type, and output inventory feature data. The supply chain key data includes historical supply chain index data, current Inventory data and forecast sales data, the strategy parameter group is used to represent the strategy parameters corresponding to the setting link of the supply chain;

An evaluation module 620, configured to calculate a corresponding evaluation index based on the predicted inventory feature data;

The output module 630 is configured to determine that the evaluation index satisfies a preset value, and determine a supply chain strategy based on a preset strategy parameter group, inventory characteristic data and target strategy type.

In an exemplary embodiment of the present disclosure, the simulation module 610 includes: the historical supply chain index data includes at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, and historical inventory fluctuation data corresponding to various types of commodities and historical out-of-stock rate; current inventory data includes at least one of the following: current inventory product type, quantity, seasonal attributes, and inventory classification; forecasted sales data includes at least one of the following: forecasted sales of various types of goods, forecasted activity sales, forecasted activity data.

In an exemplary embodiment of the present disclosure, the simulation module 610 includes: the policy 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 corresponding to the product number of days.

In an exemplary embodiment of the present disclosure, the output module 630 is specifically configured to: when the target strategy type includes replenishment strategy, arrival strategy, and inventory balance strategy, if the target strategy type is a replenishment strategy, based on the preset Strategy parameter group and inventory characteristic data, calculate the replenishment quantity corresponding to the warehouse at each time node; if the target strategy type is arrival strategy, calculate the time when the supplier should replenish based on the preset strategy parameter group and inventory characteristic data Node, replenishment time and corresponding warehouse; if the target strategy type is an inventory balance strategy, based on the preset strategy parameter group and inventory characteristic data, determine the inventory corresponding to each warehouse at each time node.

In an exemplary embodiment of the present disclosure, the simulation module 610 is specifically configured to: based on the target strategy type, input key supply chain data and preset strategy parameter groups into the simulation model of the target strategy type to obtain the Strategy output; input the strategy output into the simulation model of the target strategy type to obtain the strategy output of the next unit duration; repeat the step of obtaining the strategy output of the next unit duration until the total duration corresponding to the strategy output is the set cycle length , taking the policy output as the predicted inventory feature data.

In an exemplary embodiment of the present disclosure, the evaluation module 620 is specifically configured to: the inventory feature data includes inventory data and sales data; based on the inventory data and sales data, calculate the out-of-stock rate corresponding to each commodity in each warehouse.

In an exemplary embodiment of the present disclosure, the output module 630 is specifically configured to: after calculating the corresponding evaluation index based on the predicted inventory feature data, if the evaluation index does not meet the preset value, reset the policy parameter group, and The key data of the supply chain are jointly input into the simulation model of the target strategy type to obtain the corresponding inventory characteristic data; determine the corresponding evaluation index of the inventory characteristic data; repeat the steps of resetting the strategy parameter group to calculate the corresponding evaluation index until the set conditions are met ; Determine the supply chain strategy based on the corresponding strategy parameter group, inventory feature data and target strategy type when the set conditions are met.

In an exemplary embodiment of the present disclosure, the output module 630 includes: the set condition includes at least one of the following: the number of times the strategy parameter group is repeatedly set reaches the set number of times; the index corresponding to the strategy parameter group satisfies a preset value.

Exemplary Computing Device

After introducing the method, medium, and apparatus of the exemplary embodiment of the present disclosure, next, the computing device of the exemplary embodiment of the present disclosure will be described with reference to FIG. 7 .

The computing device 70 shown in FIG. 7 is only an example, and should not limit the functions and scope of use of the embodiments of the present disclosure.

As shown in FIG. 7, computing device 70 takes the form of a general-purpose computing device. 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 ).

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

The 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.

The storage unit 702 may also include a program/utility 7025 having a set (at least one) of program modules 7024, such program modules 7024 including but not limited to: an operating system, one or more application programs, other program modules, and program data, Implementations of networked environments may be included in each or some combination of these examples.

Computing device 70 may also communicate with one or more external devices 704 (eg, keyboards, pointing devices, etc.). Such communication may occur through input/output (I/O) interface 705 . Also, computing device 70 can also communicate with one or more networks (eg, local area network (LAN), wide area network (WAN), and/or public networks, such as the Internet) through network adapter 706 . As shown in FIG. 7 , network adapter 706 communicates with other modules of computing device 70 via bus 703 . It should be appreciated that although not shown, 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 system, etc.

It should be noted that although several units/modules or subunits/modules of the supply chain policy determination device and the object scoring model training device are mentioned in the above detailed description, this division is only exemplary and not mandatory. Actually, according to the embodiments of the present disclosure, the features and functions of two or more units/modules described above may be embodied in one unit/module. Conversely, the features and functions of one unit/module described above can be further divided to be embodied by a plurality of units/modules.

In addition, while operations of the disclosed methods are depicted in the figures in a particular order, there is no requirement or implication that these operations must be performed in that particular order, or that all illustrated operations must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution.

Although the spirit and principles of the present disclosure have been described with reference to several specific embodiments, it should be understood that the disclosure is not limited to the specific embodiments disclosed, nor does division of aspects imply that features in these aspects cannot be combined to achieve optimal performance. Benefit, this division is only for the convenience of expression. The present disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims (10)

1. A supply chain strategy determination method, characterized in that the method comprises: 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, and the supply chain key data includes historical supply chain index data, current inventory data and predicted sales data, the strategy parameter group is used to represent the strategy parameters corresponding to the setting link of the supply chain; Calculating a corresponding evaluation index based on the inventory feature data; It is determined that the evaluation index satisfies a preset value, and a supply chain strategy is determined based on the preset strategy parameter set, inventory feature data and target strategy type. 2. The supply chain strategy determination method according to claim 1, wherein the historical supply chain index data includes at least one of the following: historical inventory data, historical sales data, historical inventory turnover data, and historical inventory fluctuation data corresponding to various types of commodities and historical out-of-stock rates; The current inventory data includes at least one of the following: current inventory commodity type, quantity, seasonal attribute, inventory classification; The forecast sales data includes at least one of the following: forecast sales of various types of commodities, forecast activity sales, and forecast activity data. 3. The supply chain strategy determination method according to claim 1, said strategy parameter group comprising 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. 4. The supply chain strategy determination method according to claim 1, said target strategy type comprising a replenishment strategy, an arrival strategy, and an inventory balance strategy; The determining the supply chain strategy based on the preset strategy parameter group, inventory characteristic data and target strategy type includes: If the target strategy type is a replenishment strategy, calculate the replenishment quantity corresponding to the warehouse at each time node based on the preset strategy parameter group and inventory feature data; If the target strategy type is an arrival strategy, based on the preset strategy parameter group and inventory feature data, calculate the time node when the supplier should replenish the goods, the replenishment time and the corresponding warehouse; If the target strategy type is an inventory balance strategy, based on the preset strategy parameter group and inventory characteristic data, determine the corresponding inventory quantity of each warehouse at each time node. 5. The supply chain strategy determination method according to any one of claims 1 to 4, wherein the key data of the supply chain and the preset strategy parameter group are input to the simulation model of the target strategy type based on the target strategy type , output forecasted inventory feature data, including: Based on the target strategy type, input the supply chain key data and the preset strategy parameter group into the simulation model of the target strategy type to obtain the strategy output per unit time; inputting the strategy output into the simulation model of the target strategy type to obtain the strategy output of the next unit duration; The step of obtaining the strategy output of the next unit duration is repeated until the total duration corresponding to the strategy output reaches the set cycle length, and the strategy output is used as the predicted inventory feature data. 6. The supply chain strategy determination method according to any one of claims 1 to 4, said inventory characteristic data comprising inventory data and sales data; The calculation of corresponding evaluation indicators based on the inventory feature data includes: Based on the inventory data and sales data, the out-of-stock rate corresponding to each commodity in each warehouse is calculated. 7. The supply chain strategy determination method according to any one of claims 1 to 4, after calculating the corresponding evaluation index based on the inventory feature data, the method further comprises: If the evaluation index does not meet the preset value, reset the strategy parameter group, and input it together with the supply chain key 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 from resetting the policy parameter group to calculating the corresponding evaluation index until the set conditions are met; The supply chain strategy is determined based on the corresponding strategy parameter group, inventory feature data and target strategy type when the set conditions are met. 8. The supply chain strategy determination method according to claim 7, said setting conditions include at least one of the following: The number of times to repeatedly set the policy parameter group reaches the set number of times; The index corresponding to the policy parameter group satisfies a preset value. 9. A computer-readable storage medium, comprising: computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to realize the The above-mentioned supply chain strategy determination method. 10. A supply chain strategy determination device, said device comprising: The simulation module is used to input key supply chain data and preset policy parameter groups into the simulation model of the target strategy type based on the target strategy type, and output inventory characteristic data, and the key supply chain data includes historical supply chain indicators data, current inventory data and forecasted sales data, the strategy parameter group is used to represent the strategy parameters corresponding to the setting link of the supply chain; An evaluation module, configured to calculate a corresponding evaluation index based on the inventory feature data; An output module, configured to determine that the evaluation index satisfies a preset value, and determine a supply chain strategy based on the preset strategy parameter set, inventory feature data, and target strategy type.

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