多类需求的动态多车辆路径问题
Dynamic Multi-Vehicle Routing with Multiple Classes of Demands
摘要：
本文研究了一类多车辆、多类需求的动态车辆路径问题。每个类的需求随时间随机地到达环境中，并且需要随机数量的现场服务，这是该类的特征。为了服务需求，其中一辆车必须行驶到需求位置并在那里停留所需的现场服务时间。提供给每个类的服务质量由该类中的需求到达与该需求的服务完成之间的预期延迟给出。我们的目标是设计一个路由策略的服务车辆，最大限度地减少每个类的延迟的凸组合。首先，我们提供了一个下界的凸组合的延迟的可实现的值。然后，我们提出了一种新的路由策略，并分析了其在重负载条件下的性能（即，当服务车辆执行现场服务所花费的时间分数接近1时）。该策略在下界的常数因子内执行（因此是最优的），其中常数仅取决于类的数量，并且与车辆的数量、需求的到达率、现场服务时间和凸组合系数无关。
英文摘要：
In this paper we study a dynamic vehicle routing problem in which there are multiple vehicles and multiple classes of demands. Demands of each class arrive in the environment randomly over time and require a random amount of on-site service that is characteristic of the class. To service a demand, one of the vehicles must travel to the demand location and remain there for the required on-site service time. The quality of service provided to each class is given by the expected delay between the arrival of a demand in the class, and that demand's service completion. The goal is to design a routing policy for the service vehicles which minimizes a convex combination of the delays for each class. First, we provide a lower bound on the achievable values of the convex combination of delays. Then, we propose a novel routing policy and analyze its performance under heavy load conditions (i.e., when the fraction of time the service vehicles spend performing on-site service approaches one). The policy performs within a constant factor of the lower bound (and thus the optimal), where the constant depends only on the number of classes, and is independent of the number of vehicles, the arrival rates of demands, the on-site service times, and the convex combination coefficients.
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。
