This work tackles a rich vehicle routing problem (VRP) problem integrating a capacitated vehicle routing problem with time windows (CVRPTW), and a service technician routing and scheduling problem (STRSP) for delivering various equipment based on customers' requests, and the subsequent installation by a number of technicians. The main objective is to reduce the overall costs of hired resources, and the total transportation costs of trucks/technicians. The problem was the topic of the fourth edition of the VeRoLog Solver Challenge in cooperation with the ORTEC company. Our contribution to research is the development of a mathematical model for this problem and a novel hyper‐heuristic algorithm to solve the problem based on a population of solutions. Experimental results on two datasets of small and real‐world size revealed the success of the hyper‐heuristic approach in finding optimal solutions in a shorter computational time, when compared to our exact model. The results of the large size dataset were also compared to the results of the eight finalists in the competition and were found to be competitive, proving the potential of our developed hyper‐heuristic framework.

中文翻译：

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来自 VeRoLog 2019 挑战的分发安装问题的精确和超启发式解决方案

这项工作解决了一个丰富的车辆路线问题 (VRP) 问题，该问题结合了具有时间窗的有能力车辆路线问题 (CVRPTW) 和服务技术人员路线和调度问题 (STRSP)，用于根据客户的要求提供各种设备，并进行后续安装由多名技术人员组成。主要目标是降低雇佣资源的总成本，以及卡车/技术人员的总运输成本。问题是与 ORTEC 公司合作的第四版 VeRoLog Solver Challenge 的主题。我们对研究的贡献是为这个问题开发了一个数学模型，并开发了一种新的超启发式算法来解决基于一组解决方案的问题。与我们的精确模型相比，在小型和真实世界大小的两个数据集上的实验结果揭示了超启发式方法在更短的计算时间内找到最佳解决方案的成功。大型数据集的结果也与比赛中八名决赛选手的结果进行了比较，并被证明具有竞争力，证明了我们开发的超启发式框架的潜力。