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Multi-objective integrated acyclic crew rostering and vehicle assignment problem in public bus transportation

机译:公共巴士运输中的多目标综合非循环乘员排班和车辆分配问题

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摘要

In this study, we try to solve a real planning problem faced in public bus transportation. It is a multi-objective integrated crew rostering and vehicle assignment problem. We model this problem as a multi-objective set partitioning problem. Most of the time, crew rostering problem with a single-objective function is considered, and the output may not satisfy some transport companies. To minimize the cost and maximize the fairness of the workload among the drivers, we define many criteria. Although crew rostering problem and its integrated versions appear in the literature, it is the first time these two problems are integrated. We propose a new multi-objective tabu search algorithm to obtain near Pareto-optimal solutions. The algorithm works with a set of solutions using parallel search. We test our algorithm for the case with ten objectives and define a method to choose solutions from the approximated efficient frontier to present to the user. We discuss the performance of our meta-heuristic approach.
机译:在这项研究中,我们试图解决公共巴士运输中面临的实际规划问题。这是一个多目标的集成人员排班和车辆分配问题。我们将此问题建模为多目标集划分问题。在大多数情况下,只考虑具有单一目标功能的人员排班问题,其输出可能无法满足某些运输公司的要求。为了最小化成本并最大程度地提高驱动程序之间的工作量公平性,我们定义了许多标准。尽管在文献中出现了船员名册问题及其集成版本,但这是这两个问题首次被整合。我们提出了一种新的多目标禁忌搜索算法来获得近似帕累托最优解。该算法与一组使用并行搜索的解决方案一起使用。我们针对有十个目标的情况测试了我们的算法,并定义了一种从近似有效边界中选择解决方案以呈现给用户的方法。我们讨论了元启发式方法的性能。

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