Research And Application Of Double Coordinate Many Particle Swarm Optimization Algorithm In TSP Problem

Particle swarm optimization is a typical swarm intelligence algorithm.It is a research hotspot because of its high efficiency and easy implementation.At present,Group segment optimization is widely used in the field of functional optimization and engineering technology,and has achieved many results.However,the research of particle swarm optimization in many fields is still in its infancy,and the algorithm itself has some shortcomings.The Supplier issue is partially compatible problems that have been extensively studied.To date,a number of different solution methods have been proposed.Particle swarm optimization has also been tried to solve the problem of traveling salesman problem,and has made great progress.However,the algorithm still has some shortcomings in the quality of the solution.Therefore,how to improve the algorithm to make it have better performance is of great significance.Based on customer paper work,this study software is applied to most of the digital digital digital dynamic and vendor traveling issues,and systematically designs the actual problem of the delivery route of the courier based on the traveling salesman problem model as follows:(1)This paper proposes a particle swarm optimization algorithm(DC-PSO)which has double group of coordination mechanism that focus on remedy the limitation of particle swarm algorithm(PSO)with low efficiency and poor stability because of the lack of diversity.This particle swarm optimization algorithm includes multiple lower work and upper decision particle swarm.The lower work particle swarm is to do the information acquisition and iteration calculation,while the top particle swarm processes information and decision-making information feedback,and double particle swarm do the teamwork.At the same time,acceleration factor with increasing distribution exponential function controls the coupling among particle swarm,so as to improve the efficiency and stability of the particle swarm when they doing the search job.The result of simulation experiment shows the effectiveness and superiority of particle swarm optimization algorithm in solving the function optimization problem.(2)Using the two-layer coordinated multi-particle swarm optimization algorithm to solve the optimization problem,the new method of solving the traveling salesman problem by using the two-layer coordinated multi-particle swarm optimization algorithm is proposed.First,the position of the particles in the algorithm is represented in terms of speed and fitness in the traveling salesman problem.Secondly,the concept of commutator and exchange order is introduced to transform the two-layer coordinated multi-particle An algorithm that effectively affects the effect,thus in the form of an algorithm traveling salesman problem.The effectiveness and efficiency of the proposed method are compared.The simulation results of the new method and the random method are carried out.The experimental results verify the feasibility and superiority of the DC PSO algorithm for solving the TSP problem.(3)For the actual production problem of low distribution efficiency of logistics end distribution,and using the advantage of double-layer coordinated multi-particle group in solving the path optimization problem,an optimized prototype system for the delivery path of the courier is designed.First of all,the demand analysis of the actual production situation of express delivery.Then,based on the needs analysis,the system analysis and design were carried out.