Particle swann optimization method for vehicle routing problem

Abstract

Vehicle Routing Problem is a well-known NP problem, many heuristic algorithms, such as Genetic algorithm, and Simulated Annealing algorithm is applied in the problem. The investigation of the performance of the Particle Swarm Optimization (PSO) method for Vehicle Routing Problem, is the main theme of the paper. Exchange minus operator is constructed to compute the particle's velocity. We use Saving algorithm and Nearest Neighbor algorithm to construct the initialization. Routing first and Cluster second is applied, PSO optimize sequence of the custom, and Nearest Neighbor algorithm optimizes every vehicle route. Two versions of PSO algorithms the global and the local version, and two construct algorithms are compared. Computational results show that the global version with hybrid construct algorithm is more efficient than the others.