Research On Model And Solution Of Enterprise Dynamic Inventory Replenishment And Delivery Based On Physical Internet

Currently,the logistic network consisting of supply chains is intertwined and complicated.The logistic network is consisted of upstream locations(factory and warehouse)controlled by suppliers and downstream locations(distribution center and sales point)controlled by retailers,which is a multi-level network structure.Once the upstream and downstream entities in the supply chain are determined,the inventory replenishment and delivery plans are also determined.The entities in the logistics network do not reach the state of universal interconnection.However,with the advent of the intelligent era,current logistics networks are difficult to meet the growing requirements of customer service.Therefore,in order to improve the service level of enterprise dynamic inventory replenishment and delivery,this paper proposes a joint replenishment strategy and a dynamic delivery strategy in Physical Interne,and designs corresponding algorithms to solve the problem.The main research works of this paper are presented as follows:(1)Research on enterprise dynamic inventory replenishment strategy in Physical Internet.In Physical Internet,all hubs have the characteristics of interconnection,opening and sharing.The purchasing point of each replenishment order is no longer predetermined.The out-of-stock PI-hubs or retailers can dynamically select suppliers or PI-hubs according to the source selection strategy.Based on these problems,this paper proposes the Installation-based and Echelon-based hybrid replenishment strategy,which applies particle swarm optimization to solve multiple replenishment plans with minimum cost,and then brings them into the simulation.Finally,Replenishment and reorder points based on the minimum cost are determined in the environment.(2)Research on enterprise dynamic inventory delivery strategy in Physical Internet.In the process of product delivery in Physical Internet,this paper proposes that not only the retailer delivers the customer,but also divides the demand level into high,medium and low demand levels,and dynamically selects the response time according to the customer’s requirements.The delivery applies clustering algorithms and particle swarm optimization to solve the shortest path based on a well-defined set of customers.(3)Proposal of models and algorithms,and verification of their effectiveness.In order to verify the feasibility of the algorithm,this paper designs a solution method combining simulation optimization and particle swarm optimization for inventory replenishment problem in Physical Internet,and the optimal replenishment strategy and minimum cost through continuous circulation.For the delivery problem,this paper uses the combination of clustering and particle swarm optimization to solve the shortest path of delivery.The simulation experiments on the examples are designed separately,and all the algorithms are coded in the Python 2019 environment.Experiments show that the proposed algorithm has better performance.This article proposes dynamic inventory replenishment and delivery issues in the Physical Internet environment,enriches the relevant theories of replenishment and delivery issues in the Physical Internet,and determines the advantages and disadvantages of each source selection strategy under the hybrid replenishment strategy and delivery in Physical Internet.The scheme provides reference and guidance for the design of the supply chain in the future Physical Internet environment,and it has certain reference value.