The Research Of Supply Chain Network Optimization Based On Particle Swarm Algorithm

Under globalization and market economic condition,Supply chain network is a basic issue in the development of modern logistics.The complex supply networks,the increasingly shorter product life cycles and the requirements of plural patterns and individuation from the customers,Manufacturing enterprises gradually formed the supply chain management mode that had multi-suppliers,multi-factories,multi-distribution centers and multi-customer.Appropriately establishing the supply chain network is the important approach to improve enterprise competition in the current demand driven competition environment.In a word,the research on optimization of supply chain network is of great significance.Based on the analysis of the structure of the supply chain network and optimization strategy,we take the inventory costs,transportation costs and cost of recycling facilities into the supply chain network optimization model.The paper builds the reproduction closed-loop supply chain optimization model and the distribution network optimization model to integrate and optimize the supply chain network.We solve the network optimization model by particle swarm optimization to get the optimal allocation of resources.The main research harvests are as follows:The paper solves the mutation and crossover operation of genetic algorithm into the particle swarm algorithm,using the improved particle swarm algorithm to solve the supply chain network in reproduction closed-loop supply chain network optimization design,and the chain management of distribution network optimization problem,with the help of a numerical example proved the feasibility of the algorithm.The paper analyzed of the supply chain network structure and opt imization strategy,further study of the application of particle swarm optimization in supply chain network optimization,supply chain network under uncertain environment through discrete coding research of secondary distribution network optimization,and the closed-loop supply chain network optimization problem,and to find the solution by the improved particle swarm algorithm.The simulation results show that the coding design is reasonable and the algorithm is ideal.And it is mainly embodied in the following two aspects:(1)We can overcome the difficulties that are large amount of time consuming,easy to fall into local optimum and hard to solve large programming problem by using the hybrid particle swarm algorithm.(2)The hybrid particle swarm algorithm could solve secondary distribution network model in a streamlined way of coding,and it could optimize and discrete the secondary distribution network by the genetic particle swarm algorithm.The algorithm could convergence faster than genetic algorithm.The simulation results show that particle swarm optimization(pso)algorithm which has good convergence,fast calculation speed and good stability can obtain the global optimal solution,and the PSO could avoid effectively the premature convergence.