The Application of Improving Particle Group Algorithm in Logistics Path Optimization

摘要

This paper mainly discusses the application of the improved particle swarm optimization in logistics distribution routing problems. Combining with the characteristics of logistics and distribution, it established a mathematical model of the distribution routing problem. Introducing the idea of genetic algorithm hybrid mutation in the particle swarm algorithms to optimize the particle swarm algorithm, the results showed that the performance of the particle swarm optimization with genetic algorithm to solve logistics routing problem is better than standard PSO. Then, the numerical simulation results show that the particle swarm optimization algorithm with cross mutation is better than the YSOPSO and LinWPSO in solving the logistics path optimization, Finally, based on a large number of experimental data, this paper discusses the influence of changing the evolution times, the number of particles and the number of cities to find the optimal path.