Recently, automation, shared use, and electrification are viewed as the “three revolutions” in the future transportation sector, and the traditional scheduled public transit system will be greatly enhanced with flexible services and autonomous vehicle scheduling capabilities. Many emerging scheduled transportation applications include the fully automatic operation system in urban rail transit, joint line planning, and timetabling for high-speed rail as well as emerging self-driving vehicle dispatching. The vehicle routing problem (VRP) holds promise for seeking an optimal set of vehicle routes and schedules to meet customers’ requirements and plays a vital role in optimizing services for feature scheduled transportation systems. Due to the difficulty of finding optimal solutions for large-scale instances, enormous research efforts have been dedicated to developing efficient algorithms, while our paper presents a unique perspective based on a time-dependent and state-dependent path searching framework. An open-source and light-weight VRP with pickup and delivery with time windows (VRPPDTW) modeling package, namely VRPLite, has been developed in this research to provide a high-quality and computationally efficient solution engine for transportation on demand applications. This paper describes the space–time–state modeling process of VRPPDTW using a hyper-network representation. This solution framework can be embedded in a column generation or Lagrangian relaxation framework to handle many general applications. A number of illustrated examples are presented to demonstrate the effectiveness of the path search algorithm under various traffic conditions and passenger travel requirements.

中文翻译：

---

带有接送服务的车辆路线选择的开源VRPLite软件包：计划运输系统的路径查找引擎

近年来，自动化，共享使用和电气化被视为未来交通运输业的“三大革命”，而灵活的服务和自动车辆调度功能将大大增强传统的定期公交系统。许多新兴的定期运输应用包括城市轨道交通中的全自动操作系统，联合线路规划，高铁时间表以及新兴的自动驾驶汽车调度。车辆路径问题（VRP）有望寻找最佳的车辆路径和时间表以满足客户的需求，并且在优化功能性计划运输系统的服务中发挥着至关重要的作用。由于难以找到大型实例的最佳解决方案，大量的研究致力于开发高效的算法，而我们的论文则提出了基于时间依赖和状态依赖的路径搜索框架的独特观点。这项研究中开发了一种带有时窗取货和交付的开源轻量级VRP（VRPPDTW）建模软件包，即VRPLite，旨在为按需运输应用提供高质量和计算效率高的解决方案引擎。本文描述了使用超网络表示的VRPPDTW的时空状态建模过程。该解决方案框架可以嵌入到列生成或拉格朗日松弛框架中，以处理许多常规应用程序。