有容车辆路径问题的舍入容量不等式的精确分离

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Networks Pub Date : 2023-09-29 DOI:10.1002/net.22183
Konstantin Pavlikov, Niels Christian Petersen, Jon Lilholt Sørensen
{"title":"有容车辆路径问题的舍入容量不等式的精确分离","authors":"Konstantin Pavlikov, Niels Christian Petersen, Jon Lilholt Sørensen","doi":"10.1002/net.22183","DOIUrl":null,"url":null,"abstract":"Abstract The family of Rounded Capacity (RC) inequalities is one of the most important sets of valid inequalities for the Capacitated Vehicle Routing Problem (CVRP). This paper considers the problem of separation of violated RC inequalities and develops an exact procedure employing mixed integer linear programming. The developed routine is demonstrated to be very efficient for small and medium‐sized problem instances. For larger‐scale problem instances, an iterative approach for exact separation of RC inequalities is developed, based upon a selective variable pricing strategy. The approach combines column and row generation and allows us to introduce variables only when they are needed, which is essential when dealing with large‐scale problem instances. A computational study demonstrates scalability of the proposed separation routines and provides exact RC‐based lower bounds to some of the publicly available unsolved CVRP instances. The same computational study provides RC‐based lower bounds for very large‐scale CVRP instances with more than 3000 locations obtained within appropriate computational time limits.","PeriodicalId":54734,"journal":{"name":"Networks","volume":"68 1","pages":"0"},"PeriodicalIF":1.6000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exact separation of the rounded capacity inequalities for the capacitated vehicle routing problem\",\"authors\":\"Konstantin Pavlikov, Niels Christian Petersen, Jon Lilholt Sørensen\",\"doi\":\"10.1002/net.22183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The family of Rounded Capacity (RC) inequalities is one of the most important sets of valid inequalities for the Capacitated Vehicle Routing Problem (CVRP). This paper considers the problem of separation of violated RC inequalities and develops an exact procedure employing mixed integer linear programming. The developed routine is demonstrated to be very efficient for small and medium‐sized problem instances. For larger‐scale problem instances, an iterative approach for exact separation of RC inequalities is developed, based upon a selective variable pricing strategy. The approach combines column and row generation and allows us to introduce variables only when they are needed, which is essential when dealing with large‐scale problem instances. A computational study demonstrates scalability of the proposed separation routines and provides exact RC‐based lower bounds to some of the publicly available unsolved CVRP instances. The same computational study provides RC‐based lower bounds for very large‐scale CVRP instances with more than 3000 locations obtained within appropriate computational time limits.\",\"PeriodicalId\":54734,\"journal\":{\"name\":\"Networks\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/net.22183\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/net.22183","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0

摘要

舍入容量不等式族是有能力车辆路径问题(CVRP)中最重要的有效不等式集之一。本文考虑了违背RC不等式的分离问题,并利用混合整数线性规划给出了一个精确的求解方法。所开发的程序对于中小型问题实例是非常有效的。对于更大规模的问题实例,基于选择性变量定价策略,开发了精确分离RC不等式的迭代方法。该方法结合了列和行生成,并允许我们仅在需要时引入变量,这在处理大规模问题实例时是必不可少的。一项计算研究证明了所提出的分离例程的可扩展性,并为一些公开可用的未解决的CVRP实例提供了精确的基于RC的下限。同样的计算研究为在适当的计算时间限制内获得超过3000个位置的超大规模CVRP实例提供了基于RC的下限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Exact separation of the rounded capacity inequalities for the capacitated vehicle routing problem
Abstract The family of Rounded Capacity (RC) inequalities is one of the most important sets of valid inequalities for the Capacitated Vehicle Routing Problem (CVRP). This paper considers the problem of separation of violated RC inequalities and develops an exact procedure employing mixed integer linear programming. The developed routine is demonstrated to be very efficient for small and medium‐sized problem instances. For larger‐scale problem instances, an iterative approach for exact separation of RC inequalities is developed, based upon a selective variable pricing strategy. The approach combines column and row generation and allows us to introduce variables only when they are needed, which is essential when dealing with large‐scale problem instances. A computational study demonstrates scalability of the proposed separation routines and provides exact RC‐based lower bounds to some of the publicly available unsolved CVRP instances. The same computational study provides RC‐based lower bounds for very large‐scale CVRP instances with more than 3000 locations obtained within appropriate computational time limits.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Networks
Networks 工程技术-计算机:硬件
CiteScore
4.40
自引率
9.50%
发文量
46
审稿时长
12 months
期刊介绍: Network problems are pervasive in our modern technological society, as witnessed by our reliance on physical networks that provide power, communication, and transportation. As well, a number of processes can be modeled using logical networks, as in the scheduling of interdependent tasks, the dating of archaeological artifacts, or the compilation of subroutines comprising a large computer program. Networks provide a common framework for posing and studying problems that often have wider applicability than their originating context. The goal of this journal is to provide a central forum for the distribution of timely information about network problems, their design and mathematical analysis, as well as efficient algorithms for carrying out optimization on networks. The nonstandard modeling of diverse processes using networks and network concepts is also of interest. Consequently, the disciplines that are useful in studying networks are varied, including applied mathematics, operations research, computer science, discrete mathematics, and economics. Networks publishes material on the analytic modeling of problems using networks, the mathematical analysis of network problems, the design of computationally efficient network algorithms, and innovative case studies of successful network applications. We do not typically publish works that fall in the realm of pure graph theory (without significant algorithmic and modeling contributions) or papers that deal with engineering aspects of network design. Since the audience for this journal is then necessarily broad, articles that impact multiple application areas or that creatively use new or existing methodologies are especially appropriate. We seek to publish original, well-written research papers that make a substantive contribution to the knowledge base. In addition, tutorial and survey articles are welcomed. All manuscripts are carefully refereed.
期刊最新文献
Finding conserved low‐diameter subgraphs in social and biological networks A survey on optimization studies of group centrality metrics A heuristic with a performance guarantee for the commodity constrained split delivery vehicle routing problem Selecting fast algorithms for the capacitated vehicle routing problem with machine learning techniques Three network design problems for community energy storage
×
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