带时间窗的车辆计划最优链接
Optimal Chaining of Vehicle Plans with Time Windows
AI总结：
本文针对按需出行中的计划链接问题，提出一种考虑时间窗延迟的最优车辆计划链接方法，并证明其最优性，实验表明其在静态拨号乘车问题中优于启发式基线且计算开销可控。
摘要：
为了解决按需出行（Mobility-on-Demand，MoD）领域中的问题，我们通常需要将车辆计划连接成跨越更长时间的计划，这一过程我们称之为计划链接（plan chaining）。正如我们在本文中所展示的，计划链接既可以用于缩减 MoD 提供商的车辆规模（车队规模问题），也可以通过为 MoD 系统提供高质量的车辆调度方案来减少总行驶距离。最近，已有研究提出了一种利用该原理来解决车队规模问题的方法。该方法不考虑计划的时间灵活性。相反，计划在时间上是固定的，不能被延迟。然而，时间灵活性是所有带时间窗的车辆问题的基本属性。本文提出了一种新的计划链接形式化方法，该方法考虑了时间窗所允许的延迟，并给出了相应的求解方法。此外，我们证明了所提出的计划链接方法是最优的，并分析了其复杂度。最后，我们列举了一些实际应用，并针对其中一个应用进行了演示：一种用于求解静态拨号乘车问题（dial-a-ride problem）的新型启发式车辆调度方法。演示结果表明，对于大多数无法求得最优解的实例，我们所提出的方法比两个启发式基线方法提供了更好的解。同时，与基线方法相比，我们的方法并不需要最大的计算时间。因此，我们得出结论：所提出的最优链接方法不仅在理论上可靠，而且在实际中具有适用性。
英文摘要：
For solving problems from the domain of Mobility-on-Demand (MoD), we often need to connect vehicle plans into plans spanning longer time, a process we call plan chaining. As we show in this work, chaining of the plans can be used to reduce the size of MoD providers' fleet (fleet-sizing problem) but also to reduce the total driven distance by providing high-quality vehicle dispatching solutions in MoD systems. Recently, a solution that uses this principle has been proposed to solve the fleet-sizing problem. The method does not consider the time flexibility of the plans. Instead, plans are fixed in time and cannot be delayed. However, time flexibility is an essential property of all vehicle problems with time windows. This work presents a new plan chaining formulation that considers delays as allowed by the time windows and a solution method for solving it. Moreover, we prove that the proposed plan chaining method is optimal, and we analyze its complexity. Finally, we list some practical applications and perform a demonstration for one of them: a new heuristic vehicle dispatching method for solving the static dial-a-ride problem. The demonstration results show that our proposed method provides a better solution than the two heuristic baselines for the majority of instances that cannot be solved optimally. At the same time, our method does not have the largest computational time requirements compared to the baselines. Therefore, we conclude that the proposed optimal chaining method provides not only theoretically sound results but is also practically applicable.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
