多集散点车辆路径优化的混合算法

为使多集散点车辆路径优化结果全局最优,以订单为基准建立多集散点车辆路径优化模型.采用粒子群算法与改进蚁群算法组成的混合优化算法求解模型.由粒子群算法的粒子位置向量得到每辆车所需运送的订单号,用蚁群算法优化单车路径,根据优化的总路径评价和筛选粒子,直到满足终止条件.该模型和混合算法是所有车辆对所有订单节点的路径优化,突破了多仓库问题直接或间接转化为多个单仓库车辆路径优化问题中的局部节点求解的限制.实例求解结果表明,用该混合算法优化的车辆总路径长度小于用蚁群算法求得的结果.

Hybrid Algorithm on Multi-Depots Vehicle Routing Problem

In order to reach a global optimization in multi-depots vehicle routing,vehicle routing models based on detail order information were established.Hybrid algorithm was composed of particle swarm optimization(PSO) and improved ant colony optimization(ACO).Order numbers for vehicles to freight were got by particle position vector,single vehicle route was got by ACO,and then evaluated and filtered particales according to optimal vehicle routes,circulated until terminate qualification.By optimizing all vehicles routing to all orders,the model and hybrid algorithm solves the problem of searching local optimal solution in the procedure so that multi-depots transform to many single depots.Illustration results showed vehicle route length by the hybrid algorithm to be less than ant colony optimization.