A new dynamic vehicle scheduling model with changeable time window is presented. An effective algorithm 19 developed lo solve the problem. This algorithm can effectively deal with bespoken demands as well as real-time demands. The time window adjustment policy, the initial routing tabu search improvement policy, and the real time demand insertion algorithm are presented. Experimental computing results show that the algorithm, compared against the time windows hard restraint algorithms, can tremendously reduce the number of rejected customers and more efficiently deal with real-timely generated dynamic demands. The proposed tabu search algorithm can significantly improve the quality of the initial solution, effectively reduce driving expenses and save transportation costs.%提出一种新的时间窗可调整的动态车辆调度模型,设计求解该问题的算法.算法能够有效地处理预约需求和实时需求,给出时间窗的调整策略、初始路径的禁忌搜索改进策略以及实时需求的插入算法.实验计算结果表明,该算法与时间窗硬约束算法相比能够大量减少被拒绝服务的顾客数量,高效地处理实时产生的动态需求.提出的禁忌搜索算法能够显著改进初始解的质量,有效减少行驶费用,降低运输成本.
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