Construction method of intelligent warehouse logistics data management platform

Abstract

The invention belongs to the technical field of intelligent logistics, and provides a construction method of an intelligent warehouse logistics data management platform. The method comprises the following steps: respectively constructing a distributed cloud layer, a software definition layer, an edge calculation layer and an Internet of Things layer for supply chain logistics; a block chain sharing network structure is constructed, so that a distributed cloud layer, a software definition layer, an edge computing layer and an Internet of Things layer realize network connection and data communication, when a user puts forward a service request, transaction records are executed based on a block chain, a path selection model preset in the cloud layer is adopted, and the service request is sent to the cloud layer. Selecting an optimal logistics distribution path from the candidate path set based on multi-standard decision analysis so as to carry out logistics distribution, and carrying out inventory demand prediction and periodic inventory control on each warehouse of a manufacturer or a supplier based on a preset inventory control model; according to the invention, the problem that a safe, credible and open supply chain logistics sharing management platform is lacked in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent logistics technology, and in particular to a method for constructing an intelligent warehousing logistics data management platform. Background Art

[0002] The adoption of digitalization in supply chain and logistics not only changes the business model, but also shifts the logistics infrastructure to a service-oriented architecture. In the supply chain, the same supplier enterprise has to face multiple different manufacturers and customers, and a manufacturer also has to correspond to multiple different suppliers. If logistics data can be shared between different enterprises, it can greatly improve logistics work, reduce warehousing pressure, and reduce logistics costs and environmental impact. However, in the existing technology, due to the lack of a secure, reliable and open shared management platform, it is difficult to share logistics data between different enterprises. Summary of the invention

[0003] In view of the above technical problems, the present invention provides a method for constructing an intelligent warehousing logistics data management platform to solve the problem of lack of a secure, reliable and open supply chain logistics sharing management platform in the prior art.

[0004] Other features and advantages of the present invention will become apparent from the following detailed description, or may be learned in part by practice of the present invention.

[0005] According to one aspect of the present invention, a method for constructing an intelligent warehousing logistics data management platform is disclosed, the method comprising: Construct a distributed cloud layer, a software-defined layer, an edge computing layer, and an Internet of Things layer for supply chain logistics respectively. The Internet of Things layer is used to connect with industrial equipment, the edge computing layer is connected to the Internet of Things layer, the cloud layer is used to execute computing processes and store data, and the software-defined layer is based on SDN and NFV technologies; Constructing a blockchain shared network structure so that the cloud layer, the software definition layer, the edge computing layer, and the Internet of Things layer can achieve network connection and data connectivity, and setting a blockchain wallet in each blockchain node. Based on the blockchain shared network, when a user makes a service request, the service request is broadcast to an adjacent central node. The central node verifies whether the service request is valid according to an internal smart contract. If valid, the corresponding service provider and service content are matched, and an external smart contract is established so that the service provider executes the service request according to the service content. After the service provider executes the service request, the delivery certificate is sent to the service proposing node and the central node, so that the blockchain tracks the process. During the service execution process, the industrial equipment generates relevant data according to the external smart contract, the edge computing layer monitors and processes the relevant data, the software definition layer dynamically allocates resources and optimizes the path of the blockchain shared network, and the cloud layer provides the resources and computing support required for the operation of the blockchain node. The user includes one of a manufacturer, a supplier, a transporter, and a customer. After matching the corresponding service provider and the service content for the customer or supplier, the central node adopts the path selection model preset in the cloud layer to select the best logistics distribution path from the candidate path set based on multi-criteria decision analysis to carry out logistics distribution. In addition, before matching the corresponding service provider and the service content for the customer or supplier, the central node performs inventory demand forecasting and periodic inventory control for each warehouse of the manufacturer or supplier based on the inventory control model preset in the cloud layer.

[0006] Furthermore, the components of the cloud layer include data storage, computing power support, account credentials, general ledger, smart contracts, APIs, miners, consensus mechanisms, events and connections. The software-defined layer includes an application plane, a control plane and a data plane combined with blockchain technology. The application plane includes different applications that communicate with each other and with hardware devices through APIs and point-to-point communications. The control plane receives instructions or requests from the application plane and forwards them to the components of the cloud layer, as well as extracts network information of hardware devices and feeds it back to the application plane. The data plane supports communication between data packet forwarding devices and hardware devices. When monitoring and processing the relevant data, the edge computing layer identifies the timestamp, device address, data source and destination of the relevant data to identify abnormal data, and isolates and limits the connection between the industrial equipment that generates the abnormal data and the Internet of Things layer.

[0007] Furthermore, after the service request is executed, its execution process forms a transaction, and the transaction request is broadcast to an adjacent central node. The central node verifies whether the transaction is valid according to the transaction protocol. If valid, the transaction is broadcast to other nodes of the blockchain sharing network. Within a preset time, the mining nodes of the blockchain sharing network collect all valid transactions, package them into blocks, and broadcast them to all nodes. At the same time, the software-defined layer uses miner nodes to receive the blocks and verify whether all transactions therein comply with the transaction protocol. After all transactions in the block are verified, the block is added to the blockchain based on the hash function.

[0008] Furthermore, the internal smart contract includes: Use asymmetric encryption technology to encrypt and decrypt user information; Create service records on the blockchain; Perform verification checks on transactions related to the Services; Obtain an asymmetric key from the cloud.

[0009] Furthermore, the use of asymmetric encryption technology to encrypt and decrypt user information includes: The hash value of the user information and the recipient's public key and the hash value of the user information and the recipient's private key are used for encryption with a 2048-bit asymmetric key. The hash value of the user information and the recipient's public key is SHA256, and the hash value of the user information and the recipient's private key is SHA244.

[0010] Furthermore, the selecting the best logistics distribution path from the candidate path set based on multi-criteria decision analysis includes: A total path set of all paths is defined, each path in the total path set has a related context item, the context item at least includes average speed, congestion level, distance, driver interest, and cost, an expected utility value of each path in each corresponding context item is calculated based on an expected utility function, the expected utility value is standardized, and a plurality of the standardized expected utility values ​​and the corresponding paths form a group of utility vectors, and a plurality of groups of the utility vectors constitute the candidate path set; Based on the multi-criteria decision analysis, construct a feature matrix of the m*n candidate path set, each row of the feature matrix is ​​a group of utility vectors, normalize the feature matrix to obtain multiple standard utility values, and solve the optimal solution and the worst solution of the standard utility value; Constructing a weight matrix of the evaluation criteria, wherein the weight matrix is ​​a diagonal matrix, and each primitive on the diagonal of the weight matrix represents the weight of each of the context items; According to the weight matrix, the optimal solution, and the worst solution, calculating the group utility and individual regret of each standard utility value and the optimal solution; Based on the maximum group utility strategy and the set strategy weights, calculating the performance index of each of the standard utility values ​​relative to other standard utility values; The standard utility values ​​of the group utility and the individual regret within a threshold range are selected, and then the performance indicators are sorted according to their magnitude to determine a path sorting list.

[0011] Furthermore, when calculating the performance index of each standard utility value relative to other standard utility values ​​based on the maximum group utility strategy and the set strategy weight, it includes: The performance indicator is calculated based on the group utility and the individual regret of the calculated standard utility value, the maximum and minimum values ​​of the group utilities of all the standard utility values, the minimum and maximum values ​​of the individual regrets of all the standard utility values, and the strategy weight.

[0012] Furthermore, the inventory control model includes a prediction model trained based on an artificial neural network, and the cloud layer, when performing periodic inventory control, includes: Based on the forecast model, the average daily forecast demand, average delivery cycle, standard deviation of the average daily forecast demand and the average delivery cycle, and service level corresponding to the warehouse are calculated, and the reorder point of the warehouse is calculated; The inventory level of the warehouse is checked periodically, and when the inventory level is lower than the reorder point, a reorder quantity of the warehouse is calculated so that the inventory level of the warehouse reaches a standard value.

[0013] The technical solution of the present invention has the following beneficial effects: Blockchain is used to connect the cloud layer, software-defined layer, edge computing layer, and Internet of Things layer of the management platform, and the data immutability of blockchain is used to ensure the security of the management platform; based on the definition of delivery certificates for smart contracts during the service process, the service process is managed and controlled in a regular manner; based on the path selection model, manufacturers or suppliers can optimize the distribution path when conducting logistics distribution to improve service levels, and based on the inventory control model, the inventory level of manufacturers or suppliers is controlled to improve the efficiency of the supply chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flowchart of a method for constructing an intelligent warehousing logistics data management platform in an embodiment of this specification; Figure 2It is a computer-readable storage medium storing a method for constructing an intelligent warehousing and logistics data management platform in an embodiment of this specification. DETAILED DESCRIPTION

[0015] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present invention will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present invention. However, those skilled in the art will appreciate that the technical solutions of the present invention may be practiced while omitting one or more of the specific details, or other methods, components, systems, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present invention.

[0016] In addition, the accompanying drawings are only schematic illustrations of the present invention. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0017] like Figure 1 As shown, the embodiment of this specification provides a method for constructing an intelligent warehousing logistics data management platform, and the execution subject of the method can be a terminal device such as a computer or a server. The method can specifically include the following steps S101 to S103: In step S101, a distributed cloud layer, a software-defined layer, an edge computing layer, and an Internet of Things layer are constructed for supply chain logistics respectively. The Internet of Things layer is used to connect to industrial equipment, the edge computing layer is connected to the Internet of Things layer, the cloud layer is used to execute computing processes and store data, and the software-defined layer is based on SDN and NFV technologies.

[0018] Among them, the distributed cloud layer, software-defined layer, edge computing layer, and Internet of Things layer constitute the framework of the management platform. Specifically, the cloud layer provides data storage, computing power, and blockchain infrastructure. The edge computing layer is responsible for connecting and providing limited computing power for industrial equipment to monitor data security and provide real-time communication. The Internet of Things layer is directly connected to industrial equipment and provides a direct bridge between the edge computing layer and industrial equipment. The software-defined layer is responsible for realizing the collaboration of different network devices and is constructed by software-defined networking (SDN) and network function virtualization (NFV) technologies. The cloud layer, software-defined layer, edge computing layer, and Internet of Things layer are connected to the blockchain shared network. The blockchain shared network provides a peer-to-peer network, decentralization, trust, and governance for the data management platform.

[0019] In step S102, a blockchain shared network structure is constructed so that the cloud layer, the software definition layer, the edge computing layer, and the Internet of Things layer can achieve network connection and data connectivity, and a blockchain wallet is set in each blockchain node. Based on the blockchain shared network, when a user makes a service request, the service request is broadcast to an adjacent central node. The central node verifies whether the service request is valid according to an internal smart contract. If valid, the corresponding service provider and service content are matched, and an external smart contract is established so that the service provider executes the service request according to the service content. After the service provider executes the service request, the delivery certificate is sent to the service proposing node and the central node, so that the blockchain tracks the process. During the service execution process, the industrial equipment generates relevant data according to the external smart contract, the edge computing layer monitors and processes the relevant data, the software definition layer dynamically allocates resources and optimizes the path of the blockchain shared network, and the cloud layer provides the resources and computing support required for the operation of the blockchain node. The user includes one of a manufacturer, a supplier, a transporter, and a customer.

[0020] Among them, the blockchain sharing network is mainly used to provide connection and data integration between the network and the physical environment. Secondly, the blockchain sharing network is responsible for tracking and tracing resources, so that resource owners and service requesters can obtain tracking information. Resource tracking also promotes the pay-as-you-go approach for each service and improves trust between all parties. The blockchain sharing network provides real-time connection with the cloud layer through the software-defined layer, mainly through two modules: cloud service and the blockchain wallet, wherein the cloud service communicates with the cloud network and sends / receives transactions to the network, and potential transaction / message services use the blockchain wallet.

[0021] In the blockchain sharing network, this embodiment proposes internal smart contracts, external smart contracts and delivery certificates. The smart contract function of the blockchain sharing network improves enterprise trust and provides the delivery certificate between all steps of resource sharing. For example, a node that needs to obtain any logistics service from the data management platform uses a smart contract to send a request, such as a supplier, manufacturer, transporter or customer's node, and then the service provider accepts the service through a smart contract; then, after each service is executed, the delivery certificate of the service is sent to the user. Specifically, the user first requests a service (the supplier requests the manufacturer to replenish, the manufacturer replenishes the supplier periodically, the customer places an order to the supplier, etc.), and the central node of the corresponding service provider receives this request to confirm whether this service can be executed, whether the service availability can be sent, and an internal smart contract is established between them. Then, after the user who makes the service request accepts the internal smart contract, the corresponding central node and the user start the external smart contract. In this process, the delivery certificate of each service is sent to the central node that provides the service and the node that makes the service request. This process is completed by the blockchain tracking service module in the software definition layer, so that the service provider and the user who makes the service request can track each process and resource.

[0022] In the above process, the underlying network mechanism can be summarized as follows: users use public networks and public keys to sign and send requests. After the service request is executed, the execution process forms a transaction, and the transaction request is broadcast to an adjacent central node. The central node verifies whether the transaction is valid according to the transaction protocol. If valid, the transaction is broadcast to other nodes of the blockchain sharing network. Within a preset time, the mining nodes of the blockchain sharing network collect all valid transactions, package them into blocks, and broadcast them to all nodes. At the same time, the software definition layer uses miner nodes to receive the blocks and verify whether all transactions therein comply with the transaction protocol. After all transactions in the block are verified, the block is added to the blockchain based on the hash function.

[0023] In step S103, after matching the corresponding service provider and the service content for the customer or supplier, the central node adopts the path selection model preset in the cloud layer to select the best logistics distribution path from the candidate path set based on multi-criteria decision analysis to perform logistics distribution. In addition, before matching the corresponding service provider and the service content for the customer or supplier, the central node performs inventory demand forecasting and periodic inventory control for each warehouse of the manufacturer or supplier based on the inventory control model preset in the cloud layer.

[0024] Among them, the reasonable distribution path selection is related to the logistics quality. Step S103 uses symmetric / asymmetric context items and multi-criteria decision analysis to optimize the logistics distribution path. Among them, the logistics distribution path can be from the supplier's warehouse to the customer, or from the manufacturer to the supplier. In addition, the data management platform is also configured to predict the warehouse level of suppliers and manufacturers to prevent the corresponding warehouse inventory level from being too high or too low. When it is too low, appropriate replenishment is carried out and a corresponding service request is issued to carry out logistics distribution replenishment.

[0025] In one embodiment, the components of the cloud layer include data storage, computing power support, account credentials, general ledger, smart contracts, APIs, miners, consensus mechanisms, events and connections. The software-defined layer includes an application plane, a control plane and a data plane combined with blockchain technology. The application plane includes different applications communicating with each other and hardware devices through APIs and point-to-point communications. The control plane receives instructions or requirements from the application plane and forwards them to the components of the cloud layer, and extracts network information of hardware devices and feeds it back to the application plane. The data plane supports communication between data packet forwarding devices and hardware devices. When monitoring and processing the relevant data, the edge computing layer identifies the timestamp, device address, data source and destination of the relevant data to identify abnormal data, and isolates and limits the connection between the industrial equipment that generates the abnormal data and the Internet of Things layer.

[0026] Among them, events are notifications of major modifications or operations occurring in the network, such as the execution of smart contracts or the formation of blocks; account credentials constitute the uniqueness, privacy, confidentiality and auditability of the user's login identity; APIs define the adaptation between blockchain sharing networks and enterprises, the interaction between enterprise service buses and various software; smart contracts are computer programs executed in a secure environment within the blockchain network, which encapsulate the business logic involving contract terms and conditions between various users. For example, the internal smart contracts mentioned above include: using asymmetric encryption technology to encrypt and decrypt user information, creating service records on the blockchain, performing verification checks on service-related transactions, and obtaining asymmetric keys from the cloud layer. The general ledger contains a sequence of encrypted linked blocks of transactions; the consensus mechanism is the process by which nodes in the network reach agreement on the legitimacy and validity of transactions attached to the ledger; the connection is used to reliably and securely connect the data management platform and is able to filter, aggregate or change data between the cloud, blockchain and enterprises; miners are responsible for adding transaction data to the ledger of past transactions, which is executed in the above-mentioned miner nodes; computing power support provides all relevant computing capabilities for the data management platform, such as the above-mentioned optimal logistics distribution path and inventory level control.

[0027] In addition, when the edge computing layer monitors and processes the relevant data, it specifically checks whether the configuration file of the industrial equipment is consistent with the information of the data packet received by the edge computing layer, verifies whether the timestamp, the device address, the data source and the destination match during the check, and verifies whether the configuration file falls within the corresponding time boundary, and performs integrity verification on the configuration file. The integrity verification is based on the hash value of the data packet or is completed using the immutable record on the blockchain. After the verification is successful, the data of the industrial equipment is synchronized to the blockchain network.

[0028] In one embodiment, the internal smart contract and / or the external smart contract uses asymmetric encryption technology to encrypt and decrypt user information, specifically including: The hash value of the user information and the recipient's public key and the hash value of the user information and the recipient's private key are used for encryption with a 2048-bit asymmetric key. The hash value of the user information and the recipient's public key is SHA256, and the hash value of the user information and the recipient's private key is SHA244.

[0029] Specifically, the RSA asymmetric encryption method is used to enhance the confidentiality and integrity of shared information on the blockchain network. The RSA algorithm is an asymmetric encryption algorithm in which two different keys, namely the private key and the public key, are used, and the private key is always kept private.

[0030] In one embodiment, the selecting the best logistics distribution path from the candidate path set based on multi-criteria decision analysis includes: Define the total path set of all paths, set , the total path set Each path in There is a collection of related context items , the context item set At least including average speed, congestion level, distance, driver interest, and cost. The cost includes energy cost. If the delivery route is from manufacturer to supplier, the cost should also take into account highway fees. Based on the expected utility function , calculate each path In each corresponding context item The expected utility value in , Represents a real number set, and the expected utility value is standardized, that is, Converted to the range of 0 to 1, we get ,Will and the corresponding paths form a set of utility vectors, and multiple sets of utility vectors constitute the candidate path set, and we get Once the candidate route set is obtained, the most suitable route needs to be selected from a large number of candidate routes. This embodiment adopts a multi-criteria decision analysis method. Specifically, the multi-criteria decision analysis can help users (transporters) make selection decisions by evaluating each candidate route with multiple criteria.

[0031] Based on the multi-criteria decision analysis, a feature matrix of the m*n candidate path set is constructed, each row of the feature matrix is ​​a group of utility vectors, the feature matrix is ​​normalized to obtain multiple standard utility values, and the optimal solution and the worst solution of the standard utility values ​​are solved.

[0032] Specifically, the feature matrix is ​​expressed as: ; The normalized expression of the feature matrix is: ; is the standard utility value, It is the square root of the sum of the squares of the original utility values ​​of all candidate paths on the jth feature. As a normalized scale factor, through this process, the value of each feature is converted to the same scale, allowing decision makers to more fairly compare the performance of different candidate paths on each feature.

[0033] Then the optimal solution and the worst solution are expressed as: ; ; is the optimal solution, is the optimal value of the standard utility value, is the worst solution, which is the worst value of the standard utility value, and is opposite to the optimal solution. In the formula of the optimal solution, if A collection of benefit-type features , then the ideal value is the maximum normalized value of all candidate paths on this feature ,if A collection of cost-type features , then the ideal value is the minimum normalized value of all candidate paths on this feature The worst solution formula is the opposite of the optimal solution formula.

[0034] Construct a weight matrix for the evaluation criteria. The weight matrix is ​​a diagonal matrix. Each primitive on the diagonal of the weight matrix represents the weight of each context item. The weight matrix is ​​set by the data management platform, that is, preset by the administrator. The weight matrix is ​​expressed as: According to the weight matrix, the optimal solution, and the worst solution, the group utility and personal regret of each standard utility value and the optimal solution are calculated, wherein the group utility is the candidate path The measure of the closeness to the optimal solution is expressed as: ; Personal regrets For candidate paths The measure of the maximum deviation from the optimal solution is expressed as: ; in, is the weight corresponding to feature j, obtained from the above weight matrix.

[0035] Based on the maximum group utility strategy and the set strategy weight, the performance index of each standard utility value relative to other standard utility values ​​is calculated, that is, according to the group utility and the individual regret of the calculated standard utility value, the maximum and minimum values ​​of the group utility of all the standard utility values, the minimum and maximum values ​​of the individual regret of all the standard utility values, and the strategy weight, the performance index is calculated as: ; in, is the performance index, is the strategy weight, which is generally preset to 0.5, indicating that the relative importance of the optimal solution of group utility and the personal regret of individual regret are equal. is the minimum value of group utility among all candidate paths, that is, the group utility under ideal conditions, is the maximum value of the group utility among all candidate paths, that is, the group utility in the worst case. is the minimum value of personal regret among all candidate paths, that is, the personal regret under ideal conditions, is the maximum value of personal regret among all candidate paths, that is, the personal regret in the worst case; The relative performance of candidate paths in terms of group utility and the gap between them and the optimal and worst solutions are calculated; The relative performance of the candidate paths in terms of individual regret is calculated, as is the difference between them and the best and worst solutions. The purpose of calculation is to find a balance point in multi-criteria decision analysis, that is, a solution that is acceptable under all the criteria considered. By calculating the value of the performance index of each candidate path, all paths can be sorted and the best choice can be found. It is suitable for complex decision problems with multiple conflicting criteria and can help transporters find the best path that is acceptable under all criteria.

[0036] The standard utility values ​​of the group utility and the individual regret within a threshold range are selected, and then the performance indicators are sorted according to their magnitude to determine a path sorting list.

[0037] Generally speaking, they can be directly sorted according to performance indicators. However, the impact of the setting of strategy weights on the results must be taken into consideration. Therefore, when the strategy weights are different, the sorting method can be different, for example, comprehensively considering the values ​​of S, Q, and R.

[0038] In one embodiment, the inventory control model includes a prediction model trained based on an artificial neural network, and the cloud layer, when performing periodic inventory control, includes: Based on the forecast model, the average daily forecast demand, average delivery cycle, standard deviation of the average daily forecast demand and the average delivery cycle, and service level of the warehouse are calculated, and the reorder point of the warehouse is calculated. It can be expressed as: ; in, is the daily average forecast demand, which is predicted by the forecast model trained based on artificial neural network. is the average delivery cycle, the service level is 95%, and the corresponding coefficient from the normal distribution table is .

[0039] The inventory level of the warehouse is checked periodically, and when the inventory level is lower than the reorder point, a reorder quantity of the warehouse is calculated so that the inventory level of the warehouse reaches a standard value.

[0040] From all the above embodiments, it can be seen that blockchain is used to connect the cloud layer, software definition layer, edge computing layer, and Internet of Things layer of the management platform, and the data immutability of blockchain is used to ensure the security of the management platform; based on the definition of delivery certificates of smart contracts in the service process, the service process has regular management and control; based on the path selection model, manufacturers or suppliers can optimize the distribution path when conducting logistics distribution to improve the service level, and based on the inventory control model, the inventory level of manufacturers or suppliers is controlled to improve the efficiency of the supply chain.

[0041] Based on the same idea, the exemplary embodiment of the present invention also provides a computer-readable storage medium on which a program product capable of implementing the above method of this specification is stored. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary embodiments of the present invention described in the above "System for Building an Intelligent Warehousing Logistics Data Management Platform" section of this specification.

[0042] refer to Figure 2 As shown, a program product 200 for implementing the above method according to an exemplary embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, system or device.

[0043] The program product may use 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, system or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0044] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, wherein readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, system, or device.

[0045] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0046] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0047] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal system, or a network device, etc.) to perform a method according to an exemplary implementation of the present invention.

[0048] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0049] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to an exemplary embodiment of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0050] Those skilled in the art will readily appreciate other embodiments of the invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art that are not disclosed in the present invention. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

Claims

1. A method for constructing an intelligent warehousing logistics data management platform, characterized in that: The method comprises: Construct a distributed cloud layer, a software-defined layer, an edge computing layer, and an Internet of Things layer for supply chain logistics respectively. The Internet of Things layer is used to connect with industrial equipment, the edge computing layer is connected to the Internet of Things layer, the cloud layer is used to execute computing processes and store data, and the software-defined layer is based on SDN and NFV technologies; Constructing a blockchain shared network structure so that the cloud layer, the software definition layer, the edge computing layer, and the Internet of Things layer can achieve network connection and data connectivity, and setting a blockchain wallet in each blockchain node. Based on the blockchain shared network, when a user makes a service request, the service request is broadcast to an adjacent central node. The central node verifies whether the service request is valid according to an internal smart contract. If valid, the corresponding service provider and service content are matched, and an external smart contract is established so that the service provider executes the service request according to the service content. After the service provider executes the service request, the delivery certificate is sent to the service proposing node and the central node, so that the blockchain tracks the process. During the service execution process, the industrial equipment generates relevant data according to the external smart contract, the edge computing layer monitors and processes the relevant data, the software definition layer dynamically allocates resources and optimizes the path of the blockchain shared network, and the cloud layer provides the resources and computing support required for the operation of the blockchain node. The user includes one of a manufacturer, a supplier, a transporter, and a customer. After matching the corresponding service provider and the service content for the customer or supplier, the central node adopts the path selection model preset in the cloud layer to select the best logistics distribution path from the candidate path set based on multi-criteria decision analysis to carry out logistics distribution. In addition, before matching the corresponding service provider and the service content for the customer or supplier, the central node performs inventory demand forecasting and periodic inventory control for each warehouse of the manufacturer or supplier based on the inventory control model preset in the cloud layer.

2. The method for constructing an intelligent warehousing logistics data management platform according to claim 1, characterized in that: The components of the cloud layer include data storage, computing power support, account credentials, general ledger, smart contracts, APIs, miners, consensus mechanisms, events and connections. The software-defined layer includes an application plane, a control plane and a data plane combined with blockchain technology. The application plane includes different applications that communicate with each other and with hardware devices through APIs and point-to-point communications. The control plane receives instructions or requirements from the application plane and forwards them to the components of the cloud layer, as well as extracts network information of hardware devices and feeds it back to the application plane. The data plane supports communication between data packet forwarding devices and hardware devices. When monitoring and processing the relevant data, the edge computing layer identifies the timestamp, device address, data source and destination of the relevant data to identify abnormal data, and isolates and limits the connection between the industrial equipment that generates the abnormal data and the Internet of Things layer.

3. The method for constructing an intelligent warehousing logistics data management platform according to claim 1, characterized in that: After the service request is executed, its execution process forms a transaction, and the transaction request is broadcast to an adjacent central node. The central node verifies whether the transaction is valid according to the transaction protocol. If valid, the transaction is broadcast to other nodes of the blockchain sharing network. Within a preset time, the mining nodes of the blockchain sharing network collect all valid transactions, package them into blocks, and broadcast them to all nodes. At the same time, the software-defined layer uses miner nodes to receive the blocks and verify whether all transactions therein comply with the transaction protocol. After all transactions in the block are verified, the block is added to the blockchain based on the hash function.

4. The method for constructing an intelligent warehousing logistics data management platform according to claim 1, characterized in that: The internal smart contracts include: Use asymmetric encryption technology to encrypt and decrypt user information; Create service records on the blockchain; Perform verification checks on transactions related to the Services; Obtain an asymmetric key from the cloud.

5. The method for constructing an intelligent warehousing logistics data management platform according to claim 4, characterized in that: The use of asymmetric encryption technology to encrypt and decrypt user information includes: The hash value of the user information and the recipient's public key and the hash value of the user information and the recipient's private key are used for encryption with a 2048-bit asymmetric key. The hash value of the user information and the recipient's public key is SHA256, and the hash value of the user information and the recipient's private key is SHA244.

6. The method for constructing an intelligent warehousing logistics data management platform according to claim 1, characterized in that: The method of selecting the best logistics distribution path from a set of candidate paths based on multi-criteria decision analysis includes: A total path set of all paths is defined, each path in the total path set has a related context item, the context item at least includes average speed, congestion level, distance, driver interest, and cost, an expected utility value of each path in each corresponding context item is calculated based on an expected utility function, the expected utility value is standardized, and a plurality of the standardized expected utility values ​​and the corresponding paths form a group of utility vectors, and a plurality of groups of the utility vectors constitute the candidate path set; Based on the multi-criteria decision analysis, construct a feature matrix of the m*n candidate path set, each row of the feature matrix is ​​a group of utility vectors, normalize the feature matrix to obtain multiple standard utility values, and solve the optimal solution and the worst solution of the standard utility value; Constructing a weight matrix of the evaluation criteria, wherein the weight matrix is ​​a diagonal matrix, and each primitive on the diagonal of the weight matrix represents the weight of each of the context items; According to the weight matrix, the optimal solution, and the worst solution, calculating the group utility and individual regret of each standard utility value and the optimal solution; Based on the maximum group utility strategy and the set strategy weights, calculating the performance index of each of the standard utility values ​​relative to other standard utility values; The standard utility values ​​of the group utility and the individual regret within a threshold range are selected, and then the performance indicators are sorted according to their magnitude to determine a path sorting list.

7. The method for constructing an intelligent warehousing logistics data management platform according to claim 6, characterized in that: When calculating the performance index of each standard utility value relative to other standard utility values ​​based on the maximum group utility strategy and the set strategy weight, it includes: The performance indicator is calculated based on the group utility and the individual regret of the calculated standard utility value, the maximum and minimum values ​​of the group utilities of all the standard utility values, the minimum and maximum values ​​of the individual regrets of all the standard utility values, and the strategy weight.

8. The method for constructing an intelligent warehousing logistics data management platform according to claim 1, characterized in that: The inventory control model includes a prediction model trained based on an artificial neural network. When the cloud layer performs periodic inventory control, it includes: Based on the forecast model, the average daily forecast demand, average delivery cycle, standard deviation of the average daily forecast demand and the average delivery cycle, and service level corresponding to the warehouse are calculated, and the reorder point of the warehouse is calculated; The inventory level of the warehouse is checked periodically, and when the inventory level is lower than the reorder point, a reorder quantity of the warehouse is calculated so that the inventory level of the warehouse reaches a standard value.

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