The Robust Vehicle Routing Problem with Time Window Assignments

M. Hoogeboom, Y. Adulyasak, W. Dullaert, Patrick Jaillet
{"title":"The Robust Vehicle Routing Problem with Time Window Assignments","authors":"M. Hoogeboom, Y. Adulyasak, W. Dullaert, Patrick Jaillet","doi":"10.1287/trsc.2020.1013","DOIUrl":null,"url":null,"abstract":"In practice, there are several applications in which logistics service providers determine the service time windows at the customers, for example, in parcel delivery, retail, and repair services. These companies face uncertain travel times and service times that have to be taken into account when determining the time windows and routes prior to departure. The objective of the proposed robust vehicle routing problem with time window assignments (RVRP-TWA) is to simultaneously determine routes and time window assignments such that the expected travel time and the risk of violating the time windows are minimized. We assume that the travel time probability distributions are not completely known but that some statistics, such as the mean, minimum, and maximum, can be estimated. We extend the robust framework based on the requirements’ violation index, which was originally developed for the case where the specific requirements (time windows) are given as inputs, to the case where they are also part of the decisions. The subproblem of finding the optimal time window assignment for the customers in a given route is shown to be convex, and the subgradients can be derived. The RVRP-TWA is solved by iteratively generating subgradient cuts from the subproblem that are added in a branch-and-cut fashion. Experiments address the performance of the proposed solution approach and examine the trade-off between expected travel time and risk of violating the time windows.","PeriodicalId":23247,"journal":{"name":"Transp. Sci.","volume":"64 1","pages":"395-413"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transp. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/trsc.2020.1013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

In practice, there are several applications in which logistics service providers determine the service time windows at the customers, for example, in parcel delivery, retail, and repair services. These companies face uncertain travel times and service times that have to be taken into account when determining the time windows and routes prior to departure. The objective of the proposed robust vehicle routing problem with time window assignments (RVRP-TWA) is to simultaneously determine routes and time window assignments such that the expected travel time and the risk of violating the time windows are minimized. We assume that the travel time probability distributions are not completely known but that some statistics, such as the mean, minimum, and maximum, can be estimated. We extend the robust framework based on the requirements’ violation index, which was originally developed for the case where the specific requirements (time windows) are given as inputs, to the case where they are also part of the decisions. The subproblem of finding the optimal time window assignment for the customers in a given route is shown to be convex, and the subgradients can be derived. The RVRP-TWA is solved by iteratively generating subgradient cuts from the subproblem that are added in a branch-and-cut fashion. Experiments address the performance of the proposed solution approach and examine the trade-off between expected travel time and risk of violating the time windows.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
具有时间窗分配的鲁棒车辆路径问题
在实践中,有几种应用程序中,物流服务提供商确定服务时间窗口,例如,在包裹递送、零售和维修服务中。这些公司在确定出发前的时间窗口和路线时,必须考虑到不确定的旅行时间和服务时间。提出的带时间窗的鲁棒车辆路径问题(RVRP-TWA)的目标是同时确定路线和时间窗分配,从而使期望旅行时间和违反时间窗的风险最小化。我们假设旅行时间概率分布是不完全已知的,但一些统计数据,如平均值,最小值和最大值,可以估计。我们扩展了基于需求违反索引的健壮框架,该索引最初是为特定需求(时间窗口)作为输入给出的情况开发的,到它们也是决策的一部分的情况。在给定路线上寻找顾客最优时间窗分配的子问题被证明是凸的,并且可以导出子梯度。RVRP-TWA是通过以分支-切割方式从子问题中迭代生成子梯度切割来解决的。实验解决了所提出的解决方案的性能,并检查了预期旅行时间和违反时间窗口的风险之间的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Effects of Air Quality on Housing Location: A Predictive Dynamic Continuum User-Optimal Approach Transportation in the Sharing Economy Scheduling Vehicles with Spatial Conflicts Differentiated Pricing of Shared Mobility Systems Considering Network Effects Using COVID-19 Data on Vaccine Shipments and Wastage to Inform Modeling and Decision-Making
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1