论文部分内容阅读
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。
In view of the multi-vehicle type problems widely existing in city logistics and distribution and the fuzzification of delivery schedule due to traffic conditions and so on, a dynamic fuzzy schedule based on trapezoidal fuzzy numbers is proposed to minimize the travel cost Multi-model vehicle scheduling problem model. In the problem solving, aiming at the situation that basic particle swarm optimization is easy to fall into local optimum, the chaotic local search strategy is introduced and a hybrid particle swarm optimization algorithm based on chaos optimization is proposed. Simulation results show that the algorithm is feasible and effective.