Study On Logistics Path Planning Based On Improved Particle Swarm Optimization

With the rapid development of Internet e-commerce,logistics service has gradually become an indispensable part of people's life.As the most important link in the whole process of logistics service,high performance time and low cost loss have become the key goals of logistics companies.Reasonable logistics distribution path can not only strengthen the core competitiveness of enterprises,but also provide a combustion promoter for the better and faster development of society.Based on the background of logistics distribution,this paper uses the improved particle swarm optimization algorithm to study the logistics path planning problem.As one of the most representative swarm intelligence optimization algorithms,particle swarm optimization has been widely used in solving various engineering problems and scientific research.In this paper,a particle swarm optimization algorithm with the ability of self correction and dimension by dimension learning is proposed.Firstly,a correction strategy is proposed to judge the correctness of the evolution trend of particles and make necessary intervention,so as to reduce the waste of learning time caused by randomness;secondly,on the basis of using the dimension by dimension mutation strategy,the individual optimal is used as the learning object of the optimal particles,which strengthens the relationship between the individual optimal and the group optimal,and endows the particles with more effective sources of information;finally,the optimization strategy is proposed After that,combined with the characteristics of the two strategies,the trigger time is controlled periodically to reduce the complexity and make the algorithm play a greater role.Simulation results show that the improved strategy can effectively improve the convergence speed and accuracy of PSO.Compared with other algorithms,the improved PSO algorithm has more advantages in low dimension and high dimension.Vehicle routing problem(VRP)is a combinatorial optimization problem which can be solved by heuristic intelligent algorithm.This paper studies a large number of domestic and foreign literature in the field of logistics path planning,summarizes and analyzes the VRP Problem,and establishes the mathematical model of logistics path planning according to the characteristics of logistics distribution.The improved particle swarm optimization algorithm and standard particle swarm optimization algorithm proposed in this paper are used to solve the logistics path planning problem respectively.The experimental results show that the improved particle swarm optimization algorithm proposed in this paper not only has higher convergence ability and better algorithm performance,but also can solve the logistics path planning problem more effectively.This method promotes the development and progress of swarm intelligence optimization algorithm,and provides a novel and efficient solution for logistics enterprises.