关键词: 粒子群算法, 量子粒子群算法, 交叉, 变异, 车辆路径问题

Abstract: Quantum Particles Swarm Optimization（QPSO） algorithm partly solves the shortcoming such that Particle Swarm Optimization algorithm rate of convergence is not fast enough, while in solving the Vehicle Routing Problem（VRP）. But there is still disadvantage. QPSO falls into local optimum easily. This paper proposes a hybrid Quantum Particle Swarm Optimization algorithm to solve the vehicle routing problem. It uses the QPSO to update particles of initial particle swarm; the crossover operating to particles can improve the global search ability; the mutation operating to particles can improve the local search ability. Applying Matlab as tool for simulation experiment, the experimental result shows that the improved algorithm had good performance to deal with VRP. It can avoid falling into local optimum, and it is better than QPSO and genetic algorithm.

Key words: Particles Swarm Optimization（PSO）algorithm, Quantum Particles Swarm Optimization（QPSO） algorithm, crossover, mutation, vehicle routing problem