CN114663012A - Production logistics management system and method based on block chain - Google Patents
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Abstract
The invention belongs to the technical field of blockchain technology and production logistics, and provides a production logistics management system and method based on blockchains. The system is managed by distributed storage nodes, transportation nodes and MEC nodes and is interconnected through the Internet of things network, decentralized logistics services are mutually provided among the nodes based on a block chain technology, and interaction and benefit safety delivery are completed by using an intelligent contract; when the storage node issues a transportation service request, the transportation node signed with the intelligent contract games with the storage node according to respective conditions, and then the transportation node determines that the last transportation service providing node provides transportation service; when the transportation node issues a calculation service request, the MEC node close to the transportation node provides a calculation task and obtains corresponding benefits. Compared with the traditional production logistics management system, the system has the advantages of distributed storage, high safety and reliability, easiness in tracing and the like.
Description
Technical Field
The invention belongs to the technical field of blockchain technology and production logistics, and provides a production logistics management system and method based on blockchains.
Background
With the increasing frequency of human socioeconomic activities, the position of logistics transportation in social resource circulation is more and more important as an indispensable ring in economic operation. In the traditional logistics industry, a logistics resource distribution system is mostly constructed in a centralized mode, logistics resources are managed, and logistics business process records are mainly involved; the logistics transportation resources are reasonably distributed in a warehousing enterprise and a plurality of transportation vehicles, and the aim is to select a proper transportation node from a plurality of logistics service providers so as to meet the requirements of requesters at the lowest cost.
However, as the demand and service of logistics are rapidly increased, a plurality of independent logistics service providers and consumers pursuing benefit maximization enter the logistics industry, the explosively increased traffic data volume brings new challenges to logistics resource allocation, and the traditional centralized management mode cannot meet the requirements of new business mode and safety. Meanwhile, the arrival of the era of rapid development of electronic commerce and block chain technologies provides a new development direction for the modern logistics industry, and the logistics industry is prompted to consider a distributed logistics resource allocation method to eliminate information asymmetry. And the resource utilization efficiency can be improved through information sharing between the logistics service requester and the logistics service provider.
One of the major challenges in modern logistics is the involvement of various independent entities (freight agencies, third-party logistics service providers, operators, carriers, etc.), and the sharing of data among various organizations needs to be timely, accurate, complete, and reliable. Although the centralized supply chain management mode can provide services for various organizations, in the face of increasing data volume and logistics supply requirements, the centralized warehouse management system has the problems of insufficient system capacity, poor expandability and the like, and does not provide a complete set of solutions for complete data collection and task decision, so that the centralized warehouse management system is difficult to cope with the increasingly expanded warehouse management scale in the world.
Disclosure of Invention
Based on the problems in the prior art, the invention provides a production logistics management system and method based on a block chain. By introducing the block chain technology, the great advantage is that no third party exists, most nodes mutually agree, and decentralization is realized. The blockchain may change the rules of the game of information exchange in the supply chain and may provide an account book for the immutable, decentralized recording of validated transaction data. The development of the intelligent contract technology provides possibility for the development of a block chain in the fields of the Internet of things and the like, and the intelligent contract is a computer program which automatically runs and issues to each node for verification and provides functions of application issuing, workload undertaking, task evaluation, reward distribution and the like. The logistics transaction content is executed through an intelligent contract, and safety guarantee is provided for the business process of the user through a method of prepayment and credit evaluation. Each node provides data verification and accessible records regarding transaction content information, etc. of requesters and executors are tamper-resistant. Compared with the traditional production logistics management system, the scheme has the advantages of distributed storage, high safety and reliability, easiness in tracing and the like, and the system architecture of supply chain logistics is optimized. Has good practical significance and application value.
In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect of the present invention, the present invention provides a block chain-based production logistics management system, which is managed by distributed storage nodes, transportation nodes and MEC nodes; the production logistics management system comprises storage nodes, transportation nodes and MEC nodes which are interconnected through an internet of things network, wherein decentralized logistics services are mutually provided among the nodes based on a block chain technology, interaction and benefit safety delivery are completed by using an intelligent contract, and a distributed logistics resource scheduling chain is formed; when a storage node issues a transportation service request to a distributed logistics resource scheduling chain, an intelligent contract is triggered, all transportation nodes signed with the intelligent contract game with the storage node according to respective conditions, the final transportation service providing node is determined, the transportation nodes provide transportation services, and corresponding benefits are obtained; when a transportation node issues a calculation service request to a distributed logistics resource scheduling chain, an intelligent contract is triggered, an MEC node close to the transportation node responds to the calculation service request, the transportation node receives and confirms, a calculation service relationship is established between the transportation node and the MEC node, the MEC node provides a calculation task, and corresponding benefits are obtained.
In a second aspect of the present invention, the present invention provides a method for block chain-based production logistics management, the method comprising:
the warehousing node submits a transportation task with task requirements and deposit to the distributed logistics resource scheduling chain;
the intelligent contract broadcasts the transportation tasks to all the transportation nodes, and the transportation nodes upload basic information and related certificates for executing the transportation tasks after receiving the transportation tasks and give transportation task responses;
after receiving the transportation task responses sent by a plurality of transportation nodes, the storage nodes record information, execute an iterative game algorithm, select the transportation nodes and obtain a final transportation strategy;
the selected transportation node receives the information sent by the intelligent contract determined by the storage node and starts to execute the actual cargo transportation process;
a transportation node executing a transportation task writes a calculation task into an intelligent contract, and the intelligent contract broadcasts the calculation task to a nearby MEC server;
the MEC server responds to the calculation task, the transportation node receives and confirms, the two sides establish a calculation service relationship, and the MEC server executes the calculation task;
after the transportation task is completed, the storage node pays the cost to the transportation node of the task transportation service through an intelligent contract; the shipping node pays a fee to an edge compute server that provides compute offload services through an intelligent contract.
The invention has the beneficial effects that:
the invention relates to a block chain network for linking all units of a complex production logistics system, so that all users of the system can timely and effectively receive and release logistics information, and fewer processes are processed in a transaction process. The invention provides an edge computing architecture, which is used for solving the problems of large calculated amount and complex scheduling and optimization, providing service among all Internet of things equipment in a supply chain by collecting, analyzing and processing data close to a final user, and providing an idea for logistics industry automation. The invention provides a task scheduling algorithm designed based on a block chain intelligent contract, which can provide a scheme for both freight transportation parties and effectively improve the logistics scheduling efficiency on the premise of ensuring fairness and justice. Compared with the traditional production logistics management system, the system has the advantages of distributed storage, high safety and reliability, easiness in tracing and the like, and optimizes the system architecture of supply chain logistics. Has good practical significance and application value.
Drawings
In order to make the object, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
fig. 1 is a diagram of a DLRAChain network architecture in an embodiment of the present invention;
fig. 2 is a flowchart of a method for block chain-based production logistics management in an embodiment of the present invention;
FIG. 3 is a schematic illustration of an iterative game in an embodiment of the present invention;
FIG. 4 is a diagram of an intelligent contract scheme in an embodiment of the invention;
FIG. 5 is a flow chart of a method of execution of the blockchain based production logistics management system in a preferred embodiment of the present invention;
fig. 6 is a functional diagram of a block chain-based production logistics management system in an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Aiming at the defects of the current central logistics management system, the invention introduces a block chain and an intelligent contract technology into the logistics resource allocation process, provides auxiliary support of computing capacity for the transportation nodes with limited hardware resources by combining an edge computing technology, provides a concept (DLRAChain) of a distributed logistics resource allocation chain, and supports independent decision making, fair bidding and benefit safety allocation of resource allocation participants. And constructing a system model according to different roles of DLRAChain participating members. The decision process between the logistics resource requester and the server is described as a game mode, and an iterative game algorithm is proposed to solve the game problem.
In the embodiment of the invention, the invention provides a production logistics management system based on a block chain, which is managed by distributed storage nodes, transportation nodes and MEC nodes, wherein the production logistics management system comprises the storage nodes, the transportation nodes and the MEC nodes which are interconnected through an internet of things network, decentralized logistics services are mutually provided among the nodes based on a block chain technology, interaction and benefit safety delivery are completed by using an intelligent contract, and a distributed logistics resource scheduling chain is formed; when a storage node issues a transportation service request to a distributed logistics resource scheduling chain, an intelligent contract is triggered, all transportation nodes signed with the intelligent contract game with the storage node according to respective conditions, the final transportation service providing node is determined, the transportation nodes provide transportation services, and corresponding benefits are obtained; when a transportation node issues a calculation service request to a distributed logistics resource scheduling chain, an intelligent contract is triggered, an MEC node close to the transportation node responds to the calculation service request, the transportation node receives and confirms, a calculation service relation is established between the transportation node and the MEC node, the MEC node provides a calculation task, and corresponding benefits are obtained.
Fig. 1 is a DLRAChain network architecture diagram in an embodiment of the present invention, as shown in fig. 1, the network entities include a warehousing node, a transportation node, and an MEC node, these distributed nodes are formed by interconnection of internet of things networks (e.g., 5G, V2X network), each node provides decentralized logistics services based on a block chain technology, and completes interaction and secure interest delivery by using an intelligent contract. Entities participating in the logistics resource allocation process in DLRAChain can be divided into three types, namely storage nodes, transportation nodes and MEC nodes, which are respectively used as a transmission service requester, a transmission service provider and a calculation service provider, and the benefits of each node in logistics scheduling are analyzed to establish a proper model. When the warehousing node issues a logistics service request to DLRAChain, the intelligent contract is triggered, and all the transportation nodes signed with the contract determine the final service providing node according to the respective conditions and the warehousing node game. Because the mobile transportation nodes are generally weak in computing capacity, computing services requiring tasks with larger computing capacity (such as block chain consensus algorithm and path planning) are provided by MEC nodes close to the transportation nodes in the process, the process that the MEC nodes provide computing unloading services is automatically triggered and managed by intelligent contracts, the transportation nodes obtain benefits from the warehousing nodes in the final task delivery process, and the MEC nodes obtain benefits from the transportation nodes. In the whole DLRA process, interaction information among all nodes is recorded in DLRAChain, and a distributed decentralized data recording mode ensures legal benefits of all parties in DLRAChain.
Each entity node will be described below, which includes 101-103, specifically as follows:
101. warehouses with freight requirements are registered as warehouse node accounts, and common warehouse nodes may be some production companies which want to store or transport their products and goods, or storage boxes for dispatching of goods among vehicles in factories. Each transaction request is issued by DLRAChain while a new intelligent contract is generated awaiting response from a vehicle intended to perform the task. In addition, the warehouse that issues the task must pay a subscription in advance. The transaction information is recorded on DLRAChain in the form of intelligent contracts, and the warehousing nodes submit the information of freight volume, destination and the like for a plurality of freight vehicles to choose. According to a scheduling scheme designed by the system, the intelligent contract matches the optimal freight object for warehousing according to the current freight task, and a freight strategy is formulated. When the shipment is confirmed to the destination, the warehouse pays the contracted service fee chain to the shipment.
Suppose that M warehouse nodes (warehousing nodes), N transport nodes (transportation nodes), and P MEC nodes (MEC servers) exist in the DLRAChain system, and T ═ { T1，t2，...，tNDenotes the set of transit nodes. When a task request is initiated, the related information such as freight quality of a transportation task needs to be submitted in an intelligent contract, the required transportation amount is represented as x, and the variable freight quality is represented as
Is used for representing the trend of the freight demand or freight volume increase and decrease of the warehouse which can be changed. Storage node and transport node tiThe strategy in the transaction is a proportional parameter of variable task quantity, which is expressed as mui，0≤μiLess than or equal to 1, and is used for determining the variable transportation volume proportion in the transportation process. So the warehousing node needs to pay for the transport vehicle at the price:
wherein λiA policy that represents the shipping node, i.e., unit pricing of the current total shipping volume. After the task is completed, the yield per unit mass is recorded as R. During actual transportation, transportation requesters prefer to evaluate high and credited services, so we refer to past transaction records of freight vehicles and express actual transportation income of warehousing as betaiR, corresponding transportation node tiIs expressed as betai，0≤βiLess than or equal to 1. We define UwiThe revenue function, which represents the warehouse, may be expressed as:
102. and the transport vehicle is registered as a transport node in DLRAChain and provides service for the storage node task request. As a carrier on the supply chain, is responsible for the transfer of goods of raw materials to the factory, factory to distributor, etc. Common transportation nodes may be trucks or Automated Guided Vehicles (AGVs) in a factory floor, which automatically search for tasks and execute them on time. Each time a task request is received, the transit node will independently decide whether to accept the request and calculate a transit policy. Each time a task is accepted, the transporter needs to provide its own attribute information, including the underlying vehicle attributes, as well as the current location, cargo capacity, etc. And the transport vehicle is used as a service side, the factors such as service quality, efficiency and integrity of the transport vehicle are also important information in the transportation process, the information is recorded as a credit value, and the warehousing and MEC node evaluates the credit value according to the historical transaction information of the transport vehicle. Since transportation vehicles are typically required to provide portable transportation services, onboard processor computing power is often difficult to handle with complex computing requirements. Services are sought for MEC nodes close to the transit node by means of smart contracts. Similar to the transportation task, the calculated volume offloading task is recorded on DLRAChain, requiring the vehicle to pay a subscription fee in advance. When the services such as transportation service calculation, consensus algorithm calculation and the like are completed, the transportation node pays the appointed service cost chain to the MEC node.
After receiving the task request from the warehousing node, the data information of the warehousing node needs to be provided as a response. Including current location information, vehicle base information such as vehicle model, loss, cargo capacity, etc. The strategy of the transport node in the transaction is to price the unit of the current total freight volume, which is expressed as lambdamin＜λi＜λmax. Where N represents the number of trucks participating in the same transportation task. Therefore, the forward revenue of the transportation node is mainly from the cost paid by the storage node, and can be expressed as:
the negative income is the fuel consumption in the transportation process and the calculated unloading cost of the MEC, wherein s represents the transportation distance, ciRepresenting a transit node tiLoss per unit mass per unit distance in transit. Can be expressed as:
wherein FiRepresenting a transit node tiThe fee paid to the edge computing server, α, represents the ratio of the edge server task unload unit price to the shipping task unit price.
Wherein deltaiRepresenting a transit node tiThe computational load offloaded to the MEC during the course of performing the required computational services during the task and blockchain consensus.
In summary, the utility function of a freight car can be expressed as:
103. in the transportation route, a plurality of edge computing servers are arranged to provide services for the terminal of the transport vehicle. The introduction of mobile edge computing provides rich computing resources for mobile internet of things applications to meet their demands for high computing performance and low latency. The edge server is registered as an MEC node in DLRAChain and provides computing service for the transport node. In order to confirm the transaction and guarantee the safety of DLRAChain, we require that the completion of each transaction requires the PoW consensus of partial nodes. The consensus content mainly comprises verification of the identity of each transaction executor and checking validity; confirming the completion of the transportation/calculation service, namely requiring the executor to upload a correct transaction confirmation certificate within the task deadline; checking the payment completion condition, namely completing payment according to the promissory salary relationship in the intelligent contract.
The MEC is used as a part of a logistics resource scheduling system and provides a computational power unloading service for the transportation node. After each delivery of the transport, a fee is charged to the transport vehicle. We consider server computing causesIs expressed as
Where epsilon is a loss parameter indicating the offload of the calculated amount. Similarly, we calculate the unloaded service cost with the same type definition, and set the appropriate ratio alpha of the unloading unit price of the edge server task to the unit price of the freight task according to the actual situation in consideration of the transportation pricing of the freight vehicle.
The forward revenue of the MEC server comes primarily from the payment of the shipping node, i.e.
Wherein deltaiRepresenting MEC as a transit node tiThe calculated amount provided in the current transportation task. The revenue function for the MEC is therefore:
although the game process is carried out between the warehousing node and the transportation node, the price of the transportation vehicle by the MEC service influences the income of the transportation node, so that the setting of the proportion parameter alpha is the key for the stable operation of the system and influences the final income of the MEC.
Fig. 2 is a flowchart of a block chain-based production logistics management method in an embodiment of the present invention, where the method shown in fig. 2 includes:
201. the warehousing node submits a transportation task with a task requirement and a deposit to the distributed logistics resource scheduling chain;
202. the intelligent contract broadcasts the transportation tasks to all the transportation nodes, and the transportation nodes upload basic information and related certificates for executing the transportation tasks after receiving the transportation tasks and give transportation task responses;
203. after receiving the transportation task responses sent by a plurality of transportation nodes, the storage nodes record information, execute an iterative game algorithm, select the transportation nodes and obtain a final transportation strategy;
in an embodiment of the present invention, the process of executing the iterative game algorithm may include:
step 1) respectively establishing a revenue function model of a delivery node and a revenue function model of a transportation node according to unit pricing given by the transportation node and a strategy of the storage node in transaction as a proportion parameter of variable task quantity;
wherein the revenue function model of the warehousing node is represented as:
wherein, UwiRepresenting the revenue function, λ, of a warehousing nodeiMeans that the policy of the shipping node i in the transaction is unit pricing for the current total shipping volume, and λmin＜λi＜λmaxN represents the number of transport nodes participating in the same transport task; lambda [ alpha ]minRepresenting the policy of the transportation node in the transaction as the minimum unit pricing for the current total freight volume; lambda [ alpha ]maxRepresenting the policy of the transportation node in the transaction as maximum unit pricing for the current total freight volume; mu.siRepresenting storage and transport nodes tiThe strategy in the transaction is a proportional parameter of variable task quantity, and is more than or equal to 0 muiLess than or equal to 1, corresponding to the transport node tiIs expressed as betai，0≤βiLess than or equal to 1. R is the revenue per unit mass; x is an expression of the necessary traffic volume,
is a variable freight quality.
Wherein the revenue function model of the transportation node is represented as:
wherein, Uti(λi，μi) Representing the revenue function, λ, of a transit nodeiThe strategy for expressing the transport node i in the transaction is to determine the unit of the current total freight volumeValence, and λmin＜λi＜λmaxN represents the number of transport nodes participating in the same transport task; lambda [ alpha ]minRepresenting the policy of the transportation node in the transaction as the minimum unit pricing for the current total freight volume; lambda [ alpha ]maxRepresenting the policy of the transportation node in the transaction as maximum unit pricing for the current total freight volume; gi(λi，μi) Representing a transit node tiForward gain of (C)i(λi，μi) Representing a transit node tiNegative yield of (c), s denotes the distance of transport, ciRepresenting a transit node tiLoss per unit mass per unit distance in transit, α represents the ratio of the unit price of unloading the edge server task to the unit price of the shipping task, δiRepresenting MEC as a transit node tiThe calculated amount provided in the current transportation task; x is an expression of the necessary traffic volume,
is a variable freight quality.
Step 2) calculating Nash equilibrium existing in a game stage by deriving the revenue function of the transport nodes, and determining the optimal pricing function of each transport node;
in the embodiment of the invention, the initial goods weight is given by the storage node, and the maximum benefit is achieved by solving the optimal pricing problem by the transportation node. Then, the warehousing node acquires current pricing from the transportation node, makes an optimal quantitative decision by taking the maximized utility as a target, and solves an optimization problem; to demonstrate the existence and uniqueness of nash equilibrium, the following analysis was made with respect to the variable λ, μ for both efficacy functions.
The first and second partial derivatives about λ are obtained by applying equation (2):
it is obvious that
UTIs a convex function, namely Nash equilibrium exists in the second stage of the game, and the storage optimal strategy meets the requirement at the moment
It is possible to obtain:
wherein λ isi *Expressed as an optimal pricing function; alpha is the ratio of the task unloading unit price of the edge server to the unit price of the freight task, muiRepresenting storage and transport nodes tiStrategy in transaction, namely, the proportion parameter 0 of variable task quantity is less than or equal to mu i1, x is the necessary transport quantity,
for variable freight quality, deltaiRepresenting MEC as a transit node tiThe calculated amount provided in the current transportation task.
Step 3) designing an upper boundary and a lower boundary for a strategy of the warehousing nodes in the transaction as a proportion parameter of variable task quantity, respectively substituting the upper boundary and the lower boundary into an optimal pricing function, and calculating to obtain the optimal pricing of each transportation node;
in the embodiment of the invention, the upper boundary mu and the lower boundary mu are designed for the strategy of the warehousing node in the transaction to be the proportion parameter mu of the variable task quantitymaxAnd muminAnd gradually advancing by utilizing the upper and lower boundaries in a form similar to a dichotomy, and calculating to obtain the optimal pricing of each transport node under the corresponding proportion parameters.
Step 4) substituting the optimal pricing of the upper boundary, the lower boundary and each transportation node into a profit function model of the storage node, and calculating to obtain the profit of the storage node;
step 5) updating the upper and lower boundaries corresponding to the proportion parameters by comparing the profits of the storage nodes corresponding to the upper and lower boundaries, returning to the step 3), or else, entering the step 6);
step 6) when the difference between the upper boundary and the lower boundary is smaller than a preset threshold, taking the corresponding proportional parameter as an optimal proportional parameter, bringing the optimal proportional parameter into an optimal pricing function, and calculating to obtain the optimal pricing of each transportation node;
and 7) substituting the optimal pricing of each transportation node in the step 6) and the optimal proportional parameter into a profit function model of the storage node, calculating to obtain the balanced profit of the storage node, selecting the transportation node corresponding to the maximum profit in the balanced profit of the storage node, and taking the optimal pricing of the transportation node and the optimal proportional parameter as a final transportation strategy.
In the embodiment of the present invention, the iterative game algorithm solves the game problem related to the logistics scheduling model through a limited number of iterations, that is, solves the maximum value of the revenue function in the system model, as shown in fig. 3, and the iterative game process as shown in fig. 3 may include the following processes:
the method comprises the following steps: the input of the algorithm is actual freight volume x and variable freight volume
Current transit node tiReputation value ofiThen, system parameters α, ξ are initialized.
Step two: in μd，μeTo represent an intermediate strategy in an iterative process, mumin，μmaxRepresents μiThe boundary of (2). In each iteration process, calculating the current income Uw of the warehouse through the formulas (2) and (12)i。
Step three: according to the warehousing income Uw under different freight strategiesiThe freight policy is updated until the change boundary difference of the freight policy is smaller than xi set by us.
Step four: and approximate Nash equilibrium is obtained, and the iteration number and the accuracy degree of the final strategy can be influenced by changing xi.
The iterative gaming process described above can be referred to as follows:
wherein, mudLower bound, μ, representing the updated scale parametereThe upper boundaries representing the updated proportion parameters are all intermediate strategies in the updating iteration process; mu.sminA lower boundary representing a scale parameter; mu.smaxRepresenting the upper bound of the scale parameter.
204. The selected transportation node receives the information sent by the intelligent contract determined by the storage node and starts to execute the actual cargo transportation process;
in the embodiment of the invention, after the corresponding transportation node is found out through the iterative game algorithm to execute the transportation task, the intelligent contract writes information such as corresponding optimal pricing and transportation task amount, calculation service required in the task execution process, calculation amount unloaded to the MEC in the block chain consensus process and the like, and the selected task node executes the corresponding cargo transportation process according to the intelligent contract.
205. A transportation node executing a transportation task writes a calculation task into an intelligent contract, and the intelligent contract broadcasts the calculation task to a nearby MEC server;
in an embodiment of the invention, a shipping node performing a shipping task may write a specific amount of computing tasks to an intelligent contract that broadcasts information to nearby MEC servers seeking to perform the computing tasks.
206. The MEC server responds to the calculation task, the transportation node receives and confirms, the two parties establish a calculation service relationship, and the MEC server executes the calculation task;
207. after the transportation task is completed, the storage node pays the cost to the transportation node of the task transportation service through an intelligent contract; the shipping node pays a fee to an edge compute server that provides compute offload services through an intelligent contract.
In an embodiment of the present invention, an intelligent contract scenario is shown in FIG. 4. Smart contracts are stored on the chain in the form of computer code that can be triggered at the initiation of a transaction, which are automatically executed by the relevant network entities in a predefined manner. Each smart contract has a unique address that is recorded in the blockchain ledger along with the contents of the transaction after the transaction is completed.
Step 1: the warehousing nodes with task requirements submit a transportation task with task requirements and deposit to the blockchain, and the transportation task generally comprises specific information of transportation objects, transportation distances and goods.
Step 2-3: every time a task request is received, the intelligent contract is broadcasted to all the transportation nodes, and the transportation nodes select whether to accept the task according to the self condition and upload the basic information and the related certificates for executing the task.
And 4, step 4: after receiving the task responses sent by the plurality of transportation nodes, the warehousing nodes record information and prepare for credit evaluation and task analysis.
And 5: and the storage node executes an iterative game algorithm to obtain a final transportation strategy and prepare for task delivery.
Step 6: and the selected transport nodes receive the information sent by the intelligent contract and prepare for actual cargo transport.
And 7: the warehousing node and the transportation node carry out actual cargo loading.
And 8-9: considering the computing service (such as block chain consensus algorithm, path planning and the like) needed in the course of task transportation, the transportation node writes the computation load unloading requirement into the contract, and the contract is broadcasted to the MEC server nearby by the intelligent contract.
Step 10-11: the MEC server responds to the calculation unloading task, the transportation node receives and confirms, and the two parties establish a calculation unloading service relationship.
Step 12: and (4) an edge calculation unloading process.
Step 13: and (4) the transportation node completes the actual cargo transportation through the task calculation of the MEC server.
Step 14-15: and the warehousing node pays the cost to the transportation node of the task transportation service through an intelligent contract.
Step 16-17: the shipping node pays the cost to the edge compute server providing the compute offload service by a smart contract.
Fig. 5 is a flowchart of an execution method of the blockchain-based production logistics management system in the embodiment of the invention, and as shown in fig. 5, the execution method of the system includes:
401. initializing a task and generating an intelligent contract with a new ID;
402. broadcasting a transportation task request to a transportation node, and monitoring a response;
403. inquiring whether the transportation node needs to calculate the unloading service, if so, broadcasting to the MEC node, and monitoring the response;
404. after the MEC node completes the calculation unloading task or the transportation node completes locally, the transaction is confirmed;
405. and completing the block chain consensus algorithm by other partial nodes to complete the whole transaction process.
Fig. 6 is a functional diagram of a system in an embodiment of the invention. According to the practical requirements of production logistics, a corresponding system design is provided, and the system mainly comprises the following functions:
501. the system user registration login function is realized, the system is registered by a third party authority authentication system, and the user role registration is opened and comprises a storage node, a transportation node and an MEC node;
502. the storage node and the transport node have a task issuing function, namely a transport task issuing function and a calculation unloading task issuing function, and the service provider is a transport node and an MEC node. The corresponding service request is broadcasted to the corresponding node client through the intelligent contract.
503. All nodes have a task query function, not only comprise a current ongoing task, but also provide a tracing interface for past transaction records; due to the particularity of the blockchain ledger, task transaction traceability becomes easier.
504. In order to solve the warehousing management of production logistics, the warehouse management function is designed for the warehousing nodes, all transportation transaction records can be effectively sorted, the goods are gathered, and the goods are convenient for managers to inquire and dispatch.
Therefore, the production logistics management system and method based on the block chain have the advantages of distributed storage, high safety and reliability, easiness in tracing and the like, and the system architecture of supply chain logistics is optimized. Has good practical significance and application value.
In the whole logistics resource management process, interaction information among all nodes is recorded into the DLRAChain, and the distributed decentralized data recording mode can effectively guarantee legal benefits of all parties in the DLRAChain. Compared with the traditional production logistics management system, the scheme has the advantages of distributed storage, high safety and reliability, easiness in tracing and the like, optimizes the system architecture of supply chain logistics, and has good application value.
In the description of the present invention, it is to be understood that the terms "coaxial", "bottom", "one end", "top", "middle", "other end", "upper", "one side", "top", "inner", "outer", "front", "center", "both ends", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "disposed," "connected," "fixed," "rotated," and the like are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; the terms may be directly connected or indirectly connected through an intermediate, and may be communication between two elements or interaction relationship between two elements, unless otherwise specifically limited, and the specific meaning of the terms in the present invention will be understood by those skilled in the art according to specific situations.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A production logistics management system based on a block chain is managed by distributed storage nodes, transportation nodes and MEC nodes; the production logistics management system is characterized by comprising storage nodes, transportation nodes and MEC nodes which are interconnected through an internet of things network, wherein decentralized logistics services are mutually provided among the nodes based on a block chain technology, interaction and benefit safety delivery are completed by using an intelligent contract, and a distributed logistics resource scheduling chain is formed; when a storage node issues a transportation service request to a distributed logistics resource scheduling chain, an intelligent contract is triggered, all transportation nodes signed with the intelligent contract game with the storage node according to respective conditions, a final transportation service providing node is determined, the transportation nodes provide transportation services, and corresponding benefits are obtained; when a transportation node issues a calculation service request to a distributed logistics resource scheduling chain, an intelligent contract is triggered, an MEC node close to the transportation node responds to the calculation service request, the transportation node receives and confirms, a calculation service relationship is established between the transportation node and the MEC node, the MEC node provides a calculation task, and corresponding benefits are obtained.
2. The production logistics management system based on block chain of claim 1, wherein the warehousing nodes, the transportation nodes and the MEC nodes are registered by a third party authority certification system, warehouses with freight requirements are registered as the warehousing nodes in the distributed logistics resource scheduling chain, transportation vehicles capable of providing transportation services are registered as the transportation nodes in the distributed logistics resource scheduling chain, and MEC servers capable of providing computing services are registered as the MEC nodes in the distributed logistics resource scheduling chain.
3. A block chain-based production logistics management method, the method comprising:
the warehousing node submits a transportation task with task requirements and deposit to the distributed logistics resource scheduling chain;
the intelligent contract broadcasts the transportation tasks to all the transportation nodes, and the transportation nodes upload basic information and related certificates for executing the transportation tasks after receiving the transportation tasks and give transportation task responses;
after receiving the transportation task responses sent by a plurality of transportation nodes, the storage nodes record information, execute an iterative game algorithm, select the transportation nodes and obtain a final transportation strategy;
the selected transportation node receives the information sent by the intelligent contract determined by the storage node and starts to execute the actual cargo transportation process;
a transportation node executing a transportation task writes a calculation task into an intelligent contract, and the intelligent contract broadcasts the calculation task to a nearby MEC server;
the MEC server responds to the calculation task, the transportation node receives and confirms, the two parties establish a calculation service relationship, and the MEC server executes the calculation task;
after the transportation task is completed, the warehousing node pays the cost to the transportation node of the task transportation service through an intelligent contract; the shipping node pays a fee to an edge compute server that provides compute offload services through an intelligent contract.
4. The method for block chain-based production logistics management of claim 3, wherein the executing of the iterative game algorithm, the selecting of the transportation node and the obtaining of the final transportation strategy comprise:
step 1) respectively establishing a revenue function model of a delivery node and a revenue function model of a transportation node according to unit pricing given by the transportation node and a strategy of the storage node in transaction as a proportion parameter of variable task quantity;
step 2) calculating Nash equilibrium existing in a game stage by deriving the revenue function of the transport nodes, and determining the optimal pricing function of each transport node;
step 3) designing an upper boundary and a lower boundary for a strategy of the warehousing nodes in the transaction as a proportion parameter of variable task quantity, respectively substituting the upper boundary and the lower boundary into an optimal pricing function, and calculating to obtain the optimal pricing of each transportation node;
step 4) substituting the optimal pricing of the upper and lower boundaries and each transportation node into a profit function model of the warehousing node, and calculating to obtain the profit of the warehousing node;
step 5) updating the upper and lower boundaries corresponding to the proportion parameters by comparing the profits of the storage nodes corresponding to the upper and lower boundaries, returning to the step 3), or else, entering the step 6);
step 6) when the difference between the upper boundary and the lower boundary is smaller than a preset threshold, taking the corresponding proportional parameter as an optimal proportional parameter, bringing the optimal proportional parameter into an optimal pricing function, and calculating to obtain the optimal pricing of each transportation node;
and 7) substituting the optimal pricing of each transportation node in the step 6) and the optimal proportional parameter into a profit function model of the storage node, calculating to obtain the balanced profit of the storage node, selecting the transportation node corresponding to the maximum profit in the balanced profit of the storage node, and taking the optimal pricing of the transportation node and the optimal proportional parameter as a final transportation strategy.
5. The method as claimed in claim 4, wherein the revenue function model of the warehousing node is represented as:
Max Uwi(λi，μi)
s.t.μi∈[0，1]
wherein, UwiRepresenting the revenue function, λ, of a warehousing nodeiRepresenting a transit node tiThe policy in the transaction is unit pricing for the current total freight volume, and λmin＜λi＜λmax；λminRepresenting the policy of the transportation node in the transaction as the minimum unit pricing for the current total freight volume; lambda [ alpha ]maxRepresenting that the policy of the transit node in the transaction is maximum unit pricing for the current total shipment; mu.siRepresenting storage and transport nodes tiThe strategy in the transaction is a proportional parameter of variable task quantity, and is more than or equal to 0 muiLess than or equal to 1, corresponding to the transport node tiIs expressed as betai，0≤βiLess than or equal to 1; r is the revenue per unit mass; x is the necessary transport volume and is expressed,
is a variable freight quality.
6. The method for block chain-based production logistics management of claim 4, wherein the revenue function model of the transportation node is expressed as:
Max Uti(λi，μi)
s.t.λmin＜λi＜λmax
wherein, Uti(λi，μi) Representing the revenue function, λ, of a transit nodeiRepresenting a transit node tiThe policy in the transaction is unit pricing for the current total freight volume, and λmin＜λi＜λmax；λminRepresenting the policy of the transportation node in the transaction as the minimum unit pricing for the current total freight volume; lambda [ alpha ]maxRepresenting the policy of the transportation node in the transaction as maximum unit pricing for the current total freight volume; gi(λi，μi) Representing a transit node tiForward gain of (C)i(λi，μi) Representing a transit node tiNegative yield of (c), s denotes the distance of transport, ciRepresenting a transit node tiLoss per unit mass per unit distance in transit, α represents the ratio of the unit price of unloading the edge server task to the unit price of the shipping task, δiRepresenting MEC as a transit node tiThe calculated amount provided in the current transportation task; x is an expression of the necessary traffic volume,
is a variable freight quality.
7. The block chain-based production logistics management method of claim 4, wherein the step 2) comprises performing first and second derivation on the revenue function of the transportation node respectively, determining the revenue function of the transportation node as a convex function according to the numerical range of the second derivative, thereby determining that the game has nash equilibrium at the second order, and making the first derivative equal to 0 to obtain the optimal pricing function of each transportation node, which is expressed as:
wherein λ isi *Expressed as an optimal pricing function; alpha is the ratio of the task unloading unit price of the edge server to the unit price of the freight task, muiRepresenting storage and transport nodes tiStrategy in transaction, namely, the proportion parameter 0 of variable task quantity is less than or equal to mui1, x is the necessary transport quantity,
for variable freight quality, deltaiRepresenting MEC as a transit node tiThe calculated amount provided in the current transportation task.
8. The method for block chain-based production logistics management of claim 4, wherein the update formulas of the upper and lower boundaries corresponding to the proportional parameters are respectively expressed as:
μd＝2μmin/3+μmax/3；
μe＝μmin/3+2μmax/3；
wherein, mudA lower boundary representing the updated scale parameter; mu.seAn upper boundary representing the updated scale parameter; mu.sminA lower boundary representing a scale parameter; mu.smaxRepresenting the upper bound of the scale parameter.
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