E-commerce platform supply chain optimization method and device, equipment and storage medium

Abstract

The invention discloses an e-commerce platform supply chain optimization method and device, equipment and a storage medium, and belongs to the technical field of supply chains. According to the invention, the to-be-optimized order information is obtained and the preset supply chain is called; determining customer demand information and cargo information according to the to-be-optimized order information; and optimizing the preset supply chain according to the customer demand information and the cargo information. Through the mode, each node of the supply chain is managed and optimized according to the user demand of the order and the type of goods, the user experience is improved, and the cost of the supply chain is reduced.

Description

Technical Field

[0001] The present invention relates to the field of supply chain technology, and in particular to an e-commerce platform supply chain optimization method, device, equipment and storage medium. Background Art

[0002] Currently, the supply chain of e-commerce platforms is often pre-set and remains unchanged, but this supply chain system with a fixed and supplied method is too rigid and cannot be flexibly adjusted according to the needs of users placing orders. It also leads to higher supply chain costs in different situations.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide an e-commerce platform supply chain optimization method, device, equipment and storage medium, aiming to solve the technical problem that the existing supply chain system is not flexible enough.

[0005] To achieve the above-mentioned purpose, the present invention provides an e-commerce platform supply chain optimization method, the e-commerce platform supply chain optimization method comprising:

[0006] Obtaining order information to be optimized and calling a preset supply chain, wherein the preset supply chain includes a series of supply chain nodes and the connection relationships and processes between them. The order to be optimized specifically refers to a specific order information set in the e-commerce platform that needs to be optimized for supply chain according to its user needs and goods information;

[0007] Determine customer demand information and goods information according to the order information to be optimized;

[0008] The customer demand information includes: the customer's delivery address, the customer's expected delivery time, and the customer's required goods quantity; the goods information includes: the replenishment warehouse location, the supply warehouse location, and the goods inventory;

[0009] The preset supply chain is optimized according to the customer demand information and the goods information.

[0010] Preferably, obtaining the order information to be optimized and calling the preset supply chain includes:

[0011] Pulling an order list from a server, and determining order information to be optimized according to the order list;

[0012] The order information to be optimized is imported into the supply chain determination model to determine and call the preset supply chain.

[0013] Preferably, determining the customer demand information and the goods information according to the order information to be optimized includes:

[0014] Determine the target goods according to the order information to be optimized;

[0015] According to the target goods query server, obtain goods information;

[0016] Determine order address information according to the order information to be optimized;

[0017] The customer demand information is determined according to the order address information.

[0018] Preferably, optimizing the preset supply chain according to the customer demand information and the goods information includes:

[0019] Determine the delivery address according to the customer demand information;

[0020] Obtaining a supply warehouse to be selected according to the cargo information and the preset supply chain query;

[0021] Selecting a target delivery warehouse according to the supply warehouse to be selected and the delivery address;

[0022] The preset supply chain is optimized according to the target shipping warehouse.

[0023] Preferably, the step of selecting a target delivery warehouse according to the supply warehouse to be selected and the delivery address includes:

[0024] Calculate the shipping distance, transportation cost, transportation time and replenishment cost of each supply warehouse to be selected according to the delivery address;

[0025] A target shipping warehouse is selected from each candidate supply warehouse according to the shipping distance, the transportation cost, the transportation time efficiency and the replenishment cost.

[0026] Preferably, the calculation of the shipping distance, transportation cost, transportation time efficiency and replenishment cost of each supply warehouse to be selected according to the delivery address includes:

[0027] Calculate the shipping distance of each supply warehouse to be selected according to the delivery address;

[0028] Calculate the path information from each candidate supply warehouse to the delivery address;

[0029] Calculate the transportation cost and transportation time according to the route information;

[0030] Calculate the replenishment cost of each supply warehouse to be selected based on the replenishment warehouse location information;

[0031] The transportation cost P is calculated according to the following formula:

[0032]

[0033] Where s represents the number of vehicles in the logistics transportation center; if vehicle s departs from the logistics center to customer destinations i and j, then otherwise, For each pair of customer targets i and j, the values ​​of i and j are from 1 to n;

[0034] The transportation time is determined according to the range of logistics time, and the calculation method of the range of logistics time is:

[0035] in The residual error Vi is calculated by calculating the arithmetic mean of the historical logistics timeliness according to the historical timeliness data Xi, and then the first mean square error σ is calculated according to Vi, and the arithmetic mean of the logistics timeliness data Yi with Vi>3*σ is selected according to Vi and σ. According to Yi and The calculated second mean square error;

[0036] The specific calculation formula for the replenishment cost is:

[0037]

[0038] Where K is the set of replenishment vehicles or transportation tools, K = {1, ..., p}, p is the number of transportation tools, S0 is the coordinate of the supply warehouse, S0 = {x1, ..., xn}; S1 is the coordinate of the replenishment warehouse, S1 = {y1, ..., ym}, and the travel time required for the kth transportation tool to travel from the supply warehouse coordinate i to the other supply warehouse coordinate j is t ij , when vehicle k includes the route from supply warehouse coordinate i to supply warehouse coordinate j in the replenishment path of the vehicle x ijk =1,γ i is the operation time required for the supply warehouse k to move the object to be replenished from the supply warehouse i to the transportation tool, t ij x ijk is the walking time required by executor k in the storage area, γ i x ijk is the operation time required in supply bin k, t ab y abk is the travel time in the replenishment warehouse, γ i y abk This is the operation time of the replenishment warehouse.

[0039] Preferably, optimizing the preset supply chain according to the target delivery warehouse includes:

[0040] Updating the upstream node of the preset supply chain according to the target shipping warehouse;

[0041] Determine logistics timeliness information according to the customer demand information;

[0042] The transportation method of the preset supply chain is updated according to the logistics timeliness information, and the inventory information of the preset supply chain is updated.

[0043] In addition, to achieve the above-mentioned purpose, the present invention also proposes an e-commerce platform supply chain optimization device, the e-commerce platform supply chain optimization device comprising:

[0044] Information acquisition module, used to obtain order information to be optimized and call the preset supply chain;

[0045] A demand determination module, used to determine customer demand information and goods information according to the order information to be optimized;

[0046] A supply chain optimization module is used to optimize the preset supply chain according to the customer demand information and the goods information.

[0047] In addition, to achieve the above-mentioned purpose, the present invention also proposes an e-commerce platform supply chain optimization device, which includes: a memory, a processor, and an e-commerce platform supply chain optimization program stored on the memory and running on the processor, and the e-commerce platform supply chain optimization program is configured to implement the e-commerce platform supply chain optimization method described above.

[0048] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which an e-commerce platform supply chain optimization program is stored. When the e-commerce platform supply chain optimization program is executed by a processor, the e-commerce platform supply chain optimization method described above is implemented.

[0049] The present invention obtains order information to be optimized and calls a preset supply chain; determines customer demand information and goods information according to the order information to be optimized; and optimizes the preset supply chain according to the customer demand information and the goods information. In this way, each node of the supply chain is managed and optimized according to the user demand of the order and the type of goods, thereby improving user experience and reducing supply chain costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a structural diagram of an e-commerce platform supply chain optimization device in a hardware operating environment involved in an embodiment of the present invention;

[0051] Figure 2 This is a flow chart of the first embodiment of the e-commerce platform supply chain optimization method of the present invention;

[0052] Figure 3 This is a flow chart of the second embodiment of the e-commerce platform supply chain optimization method of the present invention;

[0053] Figure 4This is a structural block diagram of the first embodiment of the e-commerce platform supply chain optimization device of the present invention.

[0054] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0055] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0056] Reference Figure 1 , Figure 1 A schematic diagram of the structure of an e-commerce platform supply chain optimization device in the hardware operating environment involved in an embodiment of the present invention.

[0057] like Figure 1 As shown, the e-commerce platform supply chain optimization device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) memory, or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0058] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the e-commerce platform supply chain optimization device, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0059] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an e-commerce platform supply chain optimization program.

[0060] exist Figure 1In the e-commerce platform supply chain optimization device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the e-commerce platform supply chain optimization device of the present invention can be set in the e-commerce platform supply chain optimization device, and the e-commerce platform supply chain optimization device calls the e-commerce platform supply chain optimization program stored in the memory 1005 through the processor 1001, and executes the e-commerce platform supply chain optimization method provided by the embodiment of the present invention.

[0061] The embodiment of the present invention provides a method for optimizing the supply chain of an e-commerce platform, referring to Figure 2 , Figure 2 It is a flow chart of a first embodiment of an e-commerce platform supply chain optimization method of the present invention.

[0062] In this embodiment, the e-commerce platform supply chain optimization method includes the following steps:

[0063] Step S10: Obtain order information to be optimized and call the preset supply chain.

[0064] In this embodiment, the execution subject of this embodiment can be the e-commerce platform supply chain optimization device, which has functions such as data processing, data communication and program running, and the e-commerce platform supply chain optimization device can be a server or a computer. Of course, it can also be other devices with similar functions, and this implementation condition does not limit this. For the sake of convenience, this implementation is described by taking the e-commerce platform supply chain optimization device as an example.

[0065] It should be noted that the preset supply chain refers to a supply chain model or framework that has been pre-set based on historical data, business rules, logistics network and other factors before supply chain optimization. This model or framework includes a series of supply chain nodes (such as suppliers, warehouses, distribution centers, etc.) and the connection relationships and processes between them.

[0066] Furthermore, in order to accurately determine the preset supply chain, step S10 includes: pulling the order list in the server, and determining the order information to be optimized based on the order list; importing the order information to be optimized into the supply chain determination model, determining and calling the preset supply chain.

[0067] It should be understood that first, the server is accessed, and the order list that currently needs to be processed is retrieved and queried in the server, and then the order information of the order to be optimized is queried in the order list. The order to be optimized can be the latest order or the order with the longest time distance in the historical record.

[0068] In a specific implementation, after the order information to be optimized is determined, the order information to be optimized is imported into the supply chain determination model to determine the preset supply chain corresponding to the various parameters and information of the order to be optimized. The supply chain determination model is a pre-trained deep learning model that can select the corresponding supply chain from the pre-stored supply chains according to the order information.

[0069] Step S20: Determine customer demand information and goods information according to the order information to be optimized.

[0070] It should be noted that customer demand information includes but is not limited to order address information, and may also include other customer requirements, such as transportation route, method, delivery time, etc. Goods information includes the type of goods, etc.

[0071] Further, in order to determine customer demand information and goods information, step S20 includes: determining the target goods according to the order information to be optimized; querying the server according to the target goods to obtain goods information; determining the order address information according to the order information to be optimized; and determining the customer demand information according to the order address information.

[0072] It should be understood that first, the goods required by the customer are determined as the target goods according to the order information to be optimized, and then the server is queried according to the type of the target goods to determine the goods information, including but not limited to the classification and storage location of the goods, warehouse, etc. Finally, the order address information is determined according to the order information to be optimized, thereby determining the customer demand information.

[0073] Step S30: Optimizing the preset supply chain according to the customer demand information and the goods information.

[0074] In specific implementation, after determining the customer demand information and goods information, the nodes of the preset supply chain are updated and optimized according to the customer demand information and goods information to achieve the effect of saving costs and improving customer experience.

[0075] This embodiment obtains the order information to be optimized and calls the preset supply chain; determines the customer demand information and the goods information according to the order information to be optimized; and optimizes the preset supply chain according to the customer demand information and the goods information. In this way, each node of the supply chain is managed and optimized according to the user demand of the order and the type of goods, thereby improving the user experience and reducing the supply chain cost.

[0076] refer to Figure 3 , Figure 3 This is a flow chart of a second embodiment of an e-commerce platform supply chain optimization method of the present invention.

[0077] Based on the first embodiment described above, the e-commerce platform supply chain optimization method of this embodiment further includes, before step S10:

[0078] Step S301: Determine the delivery address according to the customer demand information.

[0079] It should be noted that after determining the customer demand information, the delivery address should be determined first.

[0080] Step S302: Obtain a supply warehouse to be selected based on the cargo information and the preset supply chain query.

[0081] It should be understood that the cargo information is imported into the preset supply chain to determine all warehouses from which the target cargo can be shipped, namely, the supply warehouses to be selected.

[0082] Step S303: selecting a target delivery warehouse according to the supply warehouse to be selected and the delivery address.

[0083] In a specific implementation, after the supply warehouses to be selected and the delivery address are determined, the target delivery warehouse is selected from the supply warehouses to be selected.

[0084] Furthermore, in order to determine the target shipping warehouse, step S303 includes: calculating the shipping distance, transportation cost, transportation time and replenishment cost of each candidate supply warehouse according to the delivery address; and selecting the target shipping warehouse from each candidate supply warehouse according to the shipping distance, transportation cost, transportation time and replenishment cost.

[0085] In the specific implementation, the shipping distance is calculated according to the shipping address and the receiving address, the transportation cost and transportation time are determined according to the shipping distance, and the replenishment cost is determined according to the distance from the replenishment warehouse to each candidate supply warehouse. Then, combined with the specific needs of the customer, the needs include: not considering price but only considering time, only considering price but not considering time, and comprehensively considering price and time to score the shipping distance, logistics parameters and replenishment cost to determine the weight, and then the comprehensive weight of each candidate supply warehouse is calculated according to the weights of the shipping distance, transportation cost, transportation time and replenishment cost, and the candidate supply warehouse with the highest comprehensive weight is selected as the target shipping warehouse.

[0086] Specifically, the calculation method of the comprehensive weight is:

[0087] W=W1a+W2b+W3c

[0088] Among them, a is the shipping distance, b is the transportation cost, c is the transportation time, d is the replenishment cost, the replenishment cost is equal to the replenishment cost, W is the comprehensive weight, W1, W2, W3, and W4 are the shipping distance weight, transportation cost weight, transportation time weight, and replenishment cost weight respectively.

[0089] Furthermore, in order to calculate the comprehensive weight, the step of calculating the shipping distance, transportation cost, transportation time and replenishment cost of each candidate supply warehouse according to the delivery address includes: calculating the total mileage of the transportation route from the customer's delivery address to each candidate supply warehouse as the shipping distance; calculating the transportation cost and transportation time according to the path information corresponding to the shipping distance of each supply warehouse; calculating the replenishment cost of each candidate supply warehouse according to the location information of the replenishment warehouse; and finally scoring and calculating each weight according to customer demand to obtain the comprehensive weight.

[0090] It should be noted that the calculation formula for transportation cost is:

[0091]

[0092] Among them, P represents the logistics vehicle transportation cost model;

[0093] Vehicle s departs from the logistics transportation center to customer destination i, j, then otherwise h cost Indicates the transportation price of goods transported per unit weight; ij represents the Euclidean distance between customer target i and customer target j; q i represents the demand of customer target i for transported goods; S represents the number of vehicles in the logistics transportation center.

[0094] In a specific implementation, if the quantity of goods in an order is large during the vehicle transportation process, the transportation cost can also be calculated taking into account the cost of damage to the goods during transportation, specifically:

[0095]

[0096] Among them, z i represents the latest time that customer target i hopes the goods will arrive; ε i It represents the time when the transported goods of customer target i arrive.

[0097] It should be noted that when the cost of cargo damage is taken into account, the transportation cost is P+Q, otherwise it is P.

[0098] It should be understood that when calculating the transportation time efficiency, a range of logistics time efficiency must be determined first. First, the arithmetic mean of the historical logistics time efficiency data from each candidate supply warehouse to the delivery address is calculated.

[0099]

[0100] Among them, X1, X2, ..., Xn are the historical logistics data of each transportation from the selected supply warehouse to the delivery address.

[0101]

[0102] Calculate the residual error of historical logistics timeliness data.

[0103] According to the formula:

[0104]

[0105] The mean square error of the original logistics time efficiency data is calculated, and the historical logistics time efficiency data with vi>3*σ is screened out to obtain the screened logistics time efficiency data, which are recorded as Y1, Y2, Y3..., Ym.

[0106] According to the formula:

[0107]

[0108] Calculate the arithmetic mean of the second logistics time efficiency data; wherein, is the arithmetic mean of the screening logistics aging data, and Yi is the starting data when calculating the arithmetic mean of the screening logistics aging data.

[0109] The mean square error of the screening logistics time efficiency data is calculated according to the formula:

[0110]

[0111] in, is the mean square error of the screening logistics timeliness data, and the final logistics timeliness interval is:

[0112]

[0113] Finally, the transportation time is determined based on the logistics time range and the time required for the customer to expect the goods to be delivered.

[0114] It should be noted that the specific formula for calculating transportation time is:

[0115]

[0116] Where D is the time the customer expects the goods to be delivered.

[0117] It should be noted that since an order may include multiple types of goods, it is necessary to calculate the sum of the time costs from each supply warehouse to the corresponding replenishment warehouse, specifically:

[0118]

[0119] Where K is the set of replenishment vehicles or transportation tools, K = {1, ..., p}, p is the number of transportation tools, S0 is the coordinate of the supply warehouse, S0 = {x1, ..., xn}. S1 is the coordinate of the replenishment warehouse, S1 = {y1, ..., ym}. The transportation tool needs to replenish the coordinates of multiple supply warehouses, so it is necessary to plan each point in the route. The kth transportation tool (k∈K) takes t to travel from the supply warehouse coordinate i (i∈S0) to the other supply warehouse coordinate j (j∈S0). ij When vehicle k’s replenishment path includes the distance from supply warehouse coordinate i to supply warehouse coordinate j, x ijk =1, then the total walking time required by executor k in the storage area is:

[0120]

[0121] The operation time required for supply warehouse k to move the object to be replenished from supply warehouse i to the transportation tool is γi, then the total operation time required in supply warehouse k is:

[0122]

[0123] By analogy, the walking time in the replenishment warehouse can be calculated:

[0124]

[0125] Total operation time of replenishment warehouse:

[0126]

[0127] The final result is the replenishment cost.

[0128] Finally, the comprehensive weight of the warehouse to be shipped is calculated based on the weights of the shipping distance, transportation cost, transportation time and replenishment cost calculated above to determine the final target shipping warehouse.

[0129] Step S304: Optimizing the preset supply chain according to the target shipping warehouse.

[0130] It should be noted that after the target shipping warehouse is determined, the nodes of the preset supply chain are updated and optimized based on the target shipping warehouse.

[0131] Furthermore, in order to optimize the supply chain, step S304 includes: updating the upstream node of the preset supply chain according to the target shipping warehouse; determining the logistics timeliness information according to the customer demand information; updating the transportation method of the preset supply chain according to the logistics timeliness information, and updating the inventory information of the preset supply chain.

[0132] It should be understood that the various nodes of the preset supply chain are first extracted to obtain different supply chain nodes, and then the upstream nodes are updated according to the target shipping warehouse. The upstream nodes include but are not limited to: manufacturers, storage parties and shippers. The target shipping warehouse updates the shipper's node.

[0133] In the specific implementation, the logistics timeliness information, that is, the time required for the goods to be delivered, is determined according to the delivery time and transportation time requirements in the customer demand information, and finally the corresponding transportation method is selected according to the logistics timeliness information, such as air transportation, railway or road transportation. Finally, the inventory information of the preset supply chain is updated to facilitate replenishment at the upstream nodes of the supply chain.

[0134] In this embodiment, the delivery address is determined according to the customer demand information; the candidate supply warehouse is obtained according to the goods information and the preset supply chain query; the target delivery warehouse is selected according to the candidate supply warehouse and the delivery address; and the preset supply chain is optimized according to the target delivery warehouse. In this way, the delivery warehouse is selected according to customer demand, the supply chain is optimized, the logistics cost is reduced, and the user satisfaction is improved.

[0135] In addition, an embodiment of the present invention also proposes a storage medium, on which an e-commerce platform supply chain optimization program is stored. When the e-commerce platform supply chain optimization program is executed by a processor, the steps of the e-commerce platform supply chain optimization method described above are implemented.

[0136] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0137] Reference Figure 4 , Figure 4 This is a structural block diagram of the first embodiment of the e-commerce platform supply chain optimization device of the present invention.

[0138] like Figure 4 As shown, the e-commerce platform supply chain optimization device proposed in the embodiment of the present invention includes:

[0139] The information acquisition module 10 is used to obtain the order information to be optimized and call the preset supply chain.

[0140] The demand determination module 20 is used to determine customer demand information and goods information according to the order information to be optimized.

[0141] The supply chain optimization module 30 is used to optimize the preset supply chain according to the customer demand information and the goods information.

[0142] This embodiment obtains the order information to be optimized and calls the preset supply chain; determines the customer demand information and the goods information according to the order information to be optimized; and optimizes the preset supply chain according to the customer demand information and the goods information. In this way, each node of the supply chain is managed and optimized according to the user demand of the order and the type of goods, thereby improving the user experience and reducing the supply chain cost.

[0143] In one embodiment, the information acquisition module 10 is further used to pull the order list in the server, and determine the order information to be optimized based on the order list; import the order information to be optimized into the supply chain determination model, determine and call the preset supply chain.

[0144] In one embodiment, the demand determination module 20 is further used to determine the target goods according to the order information to be optimized; query the server according to the target goods to obtain goods information; determine the order address information according to the order information to be optimized; and determine the customer demand information according to the order address information.

[0145] In one embodiment, the supply chain optimization module 30 is also used to determine the delivery address based on the customer demand information; obtain a candidate supply warehouse based on the goods information and the preset supply chain query; select a target shipping warehouse based on the candidate supply warehouse and the delivery address; and optimize the preset supply chain based on the target shipping warehouse.

[0146] In one embodiment, the supply chain optimization module 30 is also used to calculate the shipping distance, transportation cost, transportation time and replenishment cost of each candidate supply warehouse based on the delivery address; and select the target shipping warehouse from the candidate supply warehouses based on the shipping distance, transportation cost, transportation time and replenishment cost.

[0147] In one embodiment, the supply chain optimization module 30 is also used to calculate the shipping distance of each candidate supply warehouse based on the delivery address; calculate the path information from each candidate supply warehouse to the delivery address; calculate the transportation cost and transportation time according to the path information; calculate the transportation cost and transportation time according to the transportation cost and the transportation time; calculate the replenishment cost of each candidate supply warehouse based on the replenishment warehouse location information.

[0148] In one embodiment, the supply chain optimization module 30 is also used to update the upstream node of the preset supply chain according to the target shipping warehouse; determine the logistics timeliness information according to the customer demand information; update the transportation method of the preset supply chain according to the logistics timeliness information, and update the inventory information of the preset supply chain.

[0149] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0150] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0151] In addition, for technical details that are not described in detail in this embodiment, please refer to the e-commerce platform supply chain optimization method provided in any embodiment of the present invention, and will not be repeated here.

[0152] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0153] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0154] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0155] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for optimizing the supply chain of an e-commerce platform, characterized in that: The e-commerce platform supply chain optimization method includes: Obtaining order information to be optimized and calling a preset supply chain, wherein the preset supply chain includes a series of supply chain nodes and the connection relationships and processes between them. The order to be optimized specifically refers to a specific order information set in the e-commerce platform that needs to be optimized for supply chain according to its user needs and goods information; Determine customer demand information and goods information according to the order information to be optimized; The customer demand information includes: the customer's delivery address, the customer's expected delivery time, and the customer's required goods quantity; the goods information includes: the replenishment warehouse location, the supply warehouse location, and the goods inventory; The preset supply chain is optimized according to the customer demand information and the goods information.

2. The e-commerce platform supply chain optimization method according to claim 1, characterized in that: The obtaining of order information to be optimized and calling a preset supply chain includes: Pulling an order list from a server, and determining order information to be optimized according to the order list; The order information to be optimized is imported into the supply chain determination model to determine and call the preset supply chain.

3. The e-commerce platform supply chain optimization method according to claim 1, characterized in that: The determining of customer demand information and goods information according to the order information to be optimized includes: Determine the target goods according to the order information to be optimized; According to the target goods query server, obtain goods information; Determine order address information according to the order information to be optimized; The customer demand information is determined according to the order address information.

4. The e-commerce platform supply chain optimization method according to claim 1, characterized in that: The optimizing the preset supply chain according to the customer demand information and the goods information includes: Determine the delivery address according to the customer demand information; Obtaining a supply warehouse to be selected according to the cargo information and the preset supply chain query; Selecting a target delivery warehouse according to the supply warehouse to be selected and the delivery address; The preset supply chain is optimized according to the target shipping warehouse.

5. The e-commerce platform supply chain optimization method according to claim 4, characterized in that: The selecting a target delivery warehouse according to the supply warehouse to be selected and the delivery address includes: Calculate the shipping distance, transportation cost, transportation time and replenishment cost of each supply warehouse to be selected according to the delivery address; A target shipping warehouse is selected from each candidate supply warehouse according to the shipping distance, the transportation cost, the transportation time efficiency and the replenishment cost.

6. The e-commerce platform supply chain optimization method according to claim 5, characterized in that: The calculation of the shipping distance, transportation cost, transportation time efficiency and replenishment cost of each supply warehouse to be selected according to the delivery address includes: Calculate the shipping distance of each supply warehouse to be selected according to the delivery address; Calculate the path information from each candidate supply warehouse to the delivery address; Calculate the transportation cost and transportation time according to the route information; Calculate the replenishment cost of each supply warehouse to be selected based on the replenishment warehouse location information; The transportation cost P is calculated according to the following formula: Where s represents the number of vehicles in the logistics center; if vehicle s departs from the logistics center to customer destinations i and j, then otherwise, For each pair of customer targets i and j, the values ​​of i and j are from 1 to n; The transportation time is determined according to the range of logistics time, and the calculation method of the range of logistics time is: in The residual error Vi is calculated by calculating the arithmetic mean of the historical logistics timeliness according to the historical timeliness data Xi, and then the first mean square error σ is calculated according to Vi, and the arithmetic mean of the logistics timeliness data Yi with Vi>3*σ is selected according to Vi and σ. According to Yi and The calculated second mean square error; The specific calculation formula for the replenishment cost is: Where K is the set of replenishment vehicles or transportation tools, K = {1, ..., p}, p is the number of transportation tools, S0 is the coordinate of the supply warehouse, S0 = {x1, ..., xn}; S1 is the coordinate of the replenishment warehouse, S1 = {y1, ..., ym}, and the travel time required for the kth transportation tool (k∈K) to travel from the supply warehouse coordinate i (i∈S0) to the other supply warehouse coordinate j (j∈S0) is t ij , when vehicle k includes the route from supply warehouse coordinate i to supply warehouse coordinate j in the replenishment path of the vehicle x ijk =1,γ i is the operation time required for the supply warehouse k to move the object to be replenished from the supply warehouse i to the transportation tool, t i x ijk is the walking time required by executor k in the storage area, γ i x ijk is the operation time required in supply bin k, t ab y abk is the travel time in the replenishment warehouse, γ i y abk This is the operation time of the replenishment warehouse.

7. The e-commerce platform supply chain optimization method according to claim 4, characterized in that: The optimizing the preset supply chain according to the target shipping warehouse includes: Updating the upstream node of the preset supply chain according to the target shipping warehouse; Determine logistics timeliness information according to the customer demand information; The transportation method of the preset supply chain is updated according to the logistics timeliness information, and the inventory information of the preset supply chain is updated.

8. An e-commerce platform supply chain optimization device, characterized in that: The e-commerce platform supply chain optimization device comprises: Information acquisition module, used to obtain order information to be optimized and call the preset supply chain; A demand determination module, used to determine customer demand information and goods information according to the order information to be optimized; A supply chain optimization module is used to optimize the preset supply chain according to the customer demand information and the goods information.

9. An e-commerce platform supply chain optimization device, characterized in that: The e-commerce platform supply chain optimization device includes: a memory, a processor, and an e-commerce platform supply chain optimization program stored in the memory and running on the processor, and the e-commerce platform supply chain optimization program is configured to implement the e-commerce platform supply chain optimization method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores an e-commerce platform supply chain optimization program, and when the e-commerce platform supply chain optimization program is executed by the processor, the e-commerce platform supply chain optimization method according to any one of claims 1 to 7 is implemented.

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