NSF/USDOT Partnership for Exploratory Research - ICSST: Dynamic and Stochastic Vehicle Dispatching with Time Dependent Travel Times: The Next Generation of Algorithms

NSF/USDOT：具有时间依赖的旅行时间的动态和随机车辆调度：下一代算法研究人员早就认识到，随机和时间依赖的旅行时间、随机的服务或处理时间以及随机的需求到达模式使得使用静态分配模型制定的计划不是最优的，而且往往是不可行的。尽管如此，替代模型和解决方法的开发进展相对缓慢。与这些不可行相关的成本可能非常高，由商用车运营商、他们的客户和整个社会承担。本研究代表了新一代路径与调度模型，该模型明确地将时间依赖和随机旅行时间、动态服务请求和随机服务时间结合在一起。感兴趣的应用是本地卡车运输业务、本地零担业务、本地收货和交付业务以及服务车队。

NSF/USDOT: Dynamic and Stochastic Vehicle Dispatching with Time Dependent Travel Times: The Next Generation of AlgorithmsResearchers have long understood that stochastic and time-dependent travel times, stochastic service or handling times and stochastic demand arrival patterns render schedules developed using static assignment models sub-optimal and often infeasible. Nonetheless, the development of alternative models and solution methods has proceeded at a relatively slow pace. The costs associated with these infeasibilities can be very high and are borne by commercial vehicle operators, their customers and society at large. This research represents a new generation of routing and scheduling models, ones that explicitly incorporate time-dependent and stochastic travel times, dynamic service requests and stochastic service times. The applications of interest are local truckload trucking operations, local less-than-truckload operations, local pickup and delivery operations and service fleets.