具有模糊行程的城市物流动态费用多车型车辆调度问题研究

Research on Multi-type Vehicle Scheduling Problem in Urban Logistics with Dynamic Delivery Cost and Fuzzy Delivery Mileage

针对城市物流配送中广泛存在的多车型问题,以及由于交通路况等因素导致的配送行程模糊化现象,给出了一种基于梯形模糊数的,以最小化行程费用为目标的具有模糊行程的动态费用多车型车辆调度问题模型。在问题求解方面,针对基本粒子群算法容易陷入局部最优的情况,引入混沌局部搜索策略,给出了一种基于混沌优化技术的混合粒子群算法。仿真实验表明,该算法具有可行性和有效性。

For the multi-type vehicle scheduling problem in cry distribution, and fuzzy delivery mileage problem caused by traffic and road factors, based on trapezoidal fuzzy number, a multi-type vehicle scheduling problem （MVSP） model having dynamic delivery cost and fuzzy delivery mileage for minimized delivery cost is introduced firstly. After that, aiming at the problems of easily getting into the local optimum of basic particle swarm optimization （PSO） algorithm, a hybrid PSO algorithm based on chaotic local optimizer is proposed for the MVSP problem above,which help the algorithm to improve its resulting precision and convergence rate. At last, through the analysis of the simulating experiment results, the feasibility and efficency of the algorithm are approved.