求解不确定车辆数车辆调度问题的蚁群算法

为同时优化所用的车辆数和行驶总路径,基于问题特征,用人工蚂蚁模拟车辆,在1次循环中利用不同蚂蚁个体的相互协作建立1个完整的解方案,使参与服务的蚂蚁数隐含了所使用的车辆数,从而能够通过优化参与服务的蚂蚁数量确定所使用的车辆数。在算法中,通过构造与算法实施相适应的禁忌表、启发函数以及为了提高搜索效率而引入中心节点虚拟需求量等策略,设计了求解具有不确定车辆数的车辆调度问题的蚁群算法。通过给定的实例对算法进行了验证,结果表明算法是有效和可行的。

Ant Colony Algorithm for Variable Fleet Dispatching Problem

An Ant Colony Algorithm（ACA） for variable fleet dispatching problem was proposed in order to optimize the number of vehicles in use and total distances traveled.In the proposed algorithm,artificial ants are used to simulate vehicles to obtain an effective schedule through the collaborations among the ants and the number of vehicles are determined by optimizing the number of servicing ants.In the designed algorithm,a tabu-list,heuristic function and hypothetical demand at the central location are introduced for improved search.Finally,a case study is carried out and the study results show that the proposed algorithm is feasible and effective.