Multi-objective optimisation for the vehicle routing problem using metaheuristics

Q3 Business, Management and Accounting
Sonu Rajak, P. Parthiban, R. Dhanalakshmi, S. Sujith
{"title":"Multi-objective optimisation for the vehicle routing problem using metaheuristics","authors":"Sonu Rajak, P. Parthiban, R. Dhanalakshmi, S. Sujith","doi":"10.1504/IJENM.2018.10014848","DOIUrl":null,"url":null,"abstract":"The capacitated vehicle routing problem is a combinatorial optimisation problem that determines a set of routes of minimum distance to deliver the goods, using a fleet of identical vehicles with restricted capacity. The objective of this article it to optimise the total distance required to deliver the goods and also the workload imbalance in terms of distances travelled by the vehicles and their loads. Due to the combinatorial in nature, it requires metaheuristic to solve these types of problems and this is a rapidly growing field of research. Here two metaheuristics such as ant colony optimisation (ACO) and simulated annealing (SA) are proposed and analysed for solving this multi-objective formulation of the vehicle routing problem. The results obtained from these two methods were compared and found that the ACO gives better results than the SA for the VRP.","PeriodicalId":39284,"journal":{"name":"International Journal of Enterprise Network Management","volume":"9 1","pages":"117-128"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Enterprise Network Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJENM.2018.10014848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 1

Abstract

The capacitated vehicle routing problem is a combinatorial optimisation problem that determines a set of routes of minimum distance to deliver the goods, using a fleet of identical vehicles with restricted capacity. The objective of this article it to optimise the total distance required to deliver the goods and also the workload imbalance in terms of distances travelled by the vehicles and their loads. Due to the combinatorial in nature, it requires metaheuristic to solve these types of problems and this is a rapidly growing field of research. Here two metaheuristics such as ant colony optimisation (ACO) and simulated annealing (SA) are proposed and analysed for solving this multi-objective formulation of the vehicle routing problem. The results obtained from these two methods were compared and found that the ACO gives better results than the SA for the VRP.
基于元启发式的车辆路径问题多目标优化
有能力的车辆路线问题是一个组合优化问题,它确定了一组最小距离的路线来交付货物,使用一组容量有限的相同车辆。本文的目的是优化交付货物所需的总距离,以及车辆及其负载行驶距离方面的工作量失衡。由于本质上的组合性,它需要元启发式来解决这些类型的问题,这是一个快速发展的研究领域。本文提出并分析了两种元启发式算法,如蚁群优化(ACO)和模拟退火(SA),以解决车辆路径问题的多目标公式。对这两种方法的结果进行了比较,发现对于VRP,ACO比SA给出了更好的结果。
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 求助全文
来源期刊
International Journal of Enterprise Network Management
International Journal of Enterprise Network Management Business, Management and Accounting-Management of Technology and Innovation
CiteScore
0.90
自引率
0.00%
发文量
28
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信