Novel particle swarm optimization algorithm withfeasibility-based rule and its application
融合可行基规则的粒子群优化算法及其应用

Basic particle swarm optimization algorithm falls into local optimum with little hindrance when it optimizes the discrete problem. To improve the performance of the standard PSO algorithm for solving discrete optimization problems, this paper proposed a novel particle swarm optimization algorithm with feasibility-based rule method. This paper used the proposed algorithm to solve the vehicle routing problem. Simulations show that proposed algorithm can obtain more powerful optimizing ability and higher optimizing precision for solving the vehicle routing problem than literature algorithms, and it has a good application value.