In transportation and logistic applications, scheduling hours of service for multiple, interdependent truck drivers to ensure compliance with regulatory resting requirements and service time windows is an extremely challenging task. Models previously designed to schedule truck drivers with interdependent routes have been capable of capturing such scenarios. However, until now, there has been no efficient way to schedule drivers when facing multiple types of interdependency constraints. To overcome this challenge, we introduce properties of truck driver schedules under working time constraints for single-day journeys. A two-stage algorithm exploits these properties to quickly produce schedules for a large number of truck routes. The algorithm minimizes the latest completion time of multiple truck schedules while ensuring that all drivers can complete their route with sufficient recovery periods and within their working hours. Computational experiments demonstrate the superiority of the approach compared to both existing algorithms and a mathematical programming approach.

在运输和物流应用中，为多个相互依赖的卡车司机安排服务时间以确保遵守监管休息要求和服务时间窗口是一项极具挑战性的任务。以前设计用于安排具有相互依赖的路线的卡车司机的模型已经能够捕捉到这种情况。然而，直到现在，当面临多种类型的相互依赖约束时，还没有一种有效的方法来调度驱动程序。为了克服这一挑战，我们在单日行程的工作时间限制下引入了卡车司机时间表的属性。两阶段算法利用这些属性快速生成大量卡车路线的时间表。该算法最大限度地减少了多辆卡车时间表的最新完成时间，同时确保所有司机都能在足够的恢复期和工作时间内完成他们的路线。计算实验证明了该方法与现有算法和数学编程方法相比的优越性。