In this paper, a new solution method is implemented to solve a bi‐objective variant of the vehicle routing problem that appears in industry and environmental enterprises. The solution involves designing a set of routes for each day in a period, in which the service frequency is a decision variable. The proposed algorithm, a muti‐start multi‐objective local search algorithm (MSMLS), minimizes total emissions produced by all vehicles and maximizes the service quality measured as the number of times that a customer is visited by a vehicle in order to be served. The MSMLS is a neighbourhood‐based metaheuristic that obtains high‐quality solutions and that is capable of achieving better performance than other competitive algorithms. Furthermore, the proposed algorithm is able to perform rapid movements thanks to the easy representation of the solutions.

中文翻译：

---

优化工业企业中出现的双目标车辆路径问题

本文采用了一种新的解决方法，以解决工业和环境企业中出现的车辆路径问题的双目标变体。该解决方案涉及在一段时间内每天设计一组路线，其中服务频率是一个决策变量。所提出的算法是多目标多目标本地搜索算法（MSMLS），可最大程度地减少所有车辆产生的总排放量，并最大程度地提高服务质量（以车辆拜访客户服务的次数来衡量）。MSMLS是一种基于邻域的元启发式方法，可获取高质量的解决方案，并且能够比其他竞争算法获得更好的性能。此外，由于解决方案的简单表示，所提出的算法能够执行快速运动。