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A robust optimization approach for the vehicle routing problem with selective backhauls
Transportation Research Part E: Logistics and Transportation Review ( IF 8.3 ) Pub Date : 2020-02-29 , DOI: 10.1016/j.tre.2020.101888
Maria João Santos , Eduardo Curcio , Mauro Henrique Mulati , Pedro Amorim , Flávio Keidi Miyazawa

The Vehicle Routing Problem with Selective Backhauls (VRPSB) aims to minimize the total routing costs minus the total revenue collected at backhaul customers. We explore a VRPSB under uncertain revenues. A deterministic VRPSB is formulated as a mixed-integer programming problem and two robust counterparts are derived. A novel method to estimate the probabilistic bounds of constraint violation is designed. A robust metaheuristic is developed, requiring little time to obtain feasible solutions with average gap of 1.40%. The robust approach studied demonstrates high potential to tackle the problem, requiring similar computing effort and maintaining the same tractability as the deterministic modeling.



中文翻译:

具有选择性回程的车辆路径问题的鲁棒优化方法

带有选择性回程的车辆路由问题(VRPSB)的目的是使总的路由成本减至从回程客户处收集的总收入减到最小。我们在收入不确定的情况下探索VRPSB。确定性VRPSB被公式化为混合整数编程问题,并得出两个健壮的对应物。设计了一种新的估计约束违反概率边界的方法。开发了强大的元启发式方法,只需很少的时间即可获得平均间隙为1.40%的可行解。研究的鲁棒方法证明了解决该问题的巨大潜力,需要类似的计算工作并保持与确定性建模相同的可处理性。

更新日期:2020-03-02
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