The VeRoLog Solver Challenge 2018–2019 of the EURO working group vehicle routing and logistics (VeRoLog) considers a multiperiod vehicle and technician routing and scheduling problem. This paper proposes a combination of large neighborhood and local search heuristics and a decomposition approach to efficiently generate competitive solutions under restricted computational resources. The interplay of the heuristics, the decomposition, and the way the search space is explored are orchestrated by an adaptive layer that explicitly considers the instance to be solved, a time limit and the performance of the computing environment. In a computational study it is shown that the method is efficient and effective, especially under tight time restrictions.

中文翻译：

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多时期车辆的自适应大变量邻域搜索和技术人员路径问题

欧元工作组路线和物流（VeRoLog）的“ VeRoLog求解器挑战2018–2019”考虑了多周期车辆和技术人员的路线和调度问题。本文提出了一种结合大型邻域和局部搜索启发式算法以及一种分解方法，以在受限的计算资源下有效生成竞争解决方案的方法。启发式，分解和探索搜索空间的方式之间的相互作用由一个自适应层精心安排，该自适应层明确考虑了要解决的实例，时限和计算环境的性能。在计算研究中表明，该方法是有效的，特别是在时间紧迫的情况下。