A review of unmanned vehicle distribution optimization models and algorithms

IF 7.4 2区 工程技术 Q1 ENGINEERING, CIVIL Journal of Traffic and Transportation Engineering-English Edition Pub Date : 2023-08-01 DOI:10.1016/j.jtte.2023.07.002
Jiao Zhao , Hui Hu , Yi Han , Yao Cai
{"title":"A review of unmanned vehicle distribution optimization models and algorithms","authors":"Jiao Zhao ,&nbsp;Hui Hu ,&nbsp;Yi Han ,&nbsp;Yao Cai","doi":"10.1016/j.jtte.2023.07.002","DOIUrl":null,"url":null,"abstract":"<div><p>With the development of globalization and artificial intelligence, as well as the outbreak of COVID-19, unmanned vehicles have played an important role in cargo distribution. In order to better analyze the research directions of unmanned vehicle distribution, this paper summarizes the models and algorithms of unmanned vehicle distribution optimization. The research results show that most of the studies have established the goal of optimizing the total costs or travel time. Many researchers have begun to study multi-objective optimization problems, but there are certain limitations, so some studies convert these problems into single-objective optimization for solving, such as converting time and energy consumption into cost, waiting time into distance, and time delay into penalty cost. With the development of unmanned vehicle distribution technology, in future research, a multi-objective model with the lowest cost, the shortest distance and the best security should be established and solved. Most studies have proposed heuristic algorithms for solving the unmanned vehicle distribution problem, and improved optimization solutions have been obtained. In order to ensure the diversity of solution methods, and give consideration to solution time and solution quality, hybrid methods with other algorithms will be a future research direction, for example, the combination of heuristic algorithm and exact algorithm. With the gradual deepening of research, integrated distribution of multiple types of unmanned equipment will become the focus of future research.</p></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":null,"pages":null},"PeriodicalIF":7.4000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Traffic and Transportation Engineering-English Edition","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S209575642300079X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

Abstract

With the development of globalization and artificial intelligence, as well as the outbreak of COVID-19, unmanned vehicles have played an important role in cargo distribution. In order to better analyze the research directions of unmanned vehicle distribution, this paper summarizes the models and algorithms of unmanned vehicle distribution optimization. The research results show that most of the studies have established the goal of optimizing the total costs or travel time. Many researchers have begun to study multi-objective optimization problems, but there are certain limitations, so some studies convert these problems into single-objective optimization for solving, such as converting time and energy consumption into cost, waiting time into distance, and time delay into penalty cost. With the development of unmanned vehicle distribution technology, in future research, a multi-objective model with the lowest cost, the shortest distance and the best security should be established and solved. Most studies have proposed heuristic algorithms for solving the unmanned vehicle distribution problem, and improved optimization solutions have been obtained. In order to ensure the diversity of solution methods, and give consideration to solution time and solution quality, hybrid methods with other algorithms will be a future research direction, for example, the combination of heuristic algorithm and exact algorithm. With the gradual deepening of research, integrated distribution of multiple types of unmanned equipment will become the focus of future research.

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
无人车配送优化模型与算法综述
随着全球化和人工智能的发展,以及新冠肺炎的爆发,无人驾驶汽车在货物配送中发挥了重要作用。为了更好地分析无人车配送的研究方向,本文总结了无人车配送优化的模型和算法。研究结果表明,大多数研究都确立了优化总成本或旅行时间的目标。许多研究人员已经开始研究多目标优化问题,但存在一定的局限性,因此一些研究将这些问题转化为单目标优化来解决,例如将时间和能耗转化为成本,将等待时间转化为距离,将时间延迟转化为惩罚成本。随着无人车配送技术的发展,在未来的研究中,应该建立并求解一个成本最低、距离最短、安全性最好的多目标模型。大多数研究都提出了求解无人车分配问题的启发式算法,并得到了改进的优化解。为了保证求解方法的多样性,并兼顾求解时间和求解质量,与其他算法的混合方法将是未来的研究方向,例如启发式算法和精确算法的结合。随着研究的逐步深入,多种类型无人设备的集成分布将成为未来研究的重点。
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
CiteScore
13.60
自引率
6.30%
发文量
402
审稿时长
15 weeks
期刊介绍: The Journal of Traffic and Transportation Engineering (English Edition) serves as a renowned academic platform facilitating the exchange and exploration of innovative ideas in the realm of transportation. Our journal aims to foster theoretical and experimental research in transportation and welcomes the submission of exceptional peer-reviewed papers on engineering, planning, management, and information technology. We are dedicated to expediting the peer review process and ensuring timely publication of top-notch research in this field.
期刊最新文献
Potential applications for composite utilization of rubber and plastic in asphalt pavements: A critical review Design equations for maximum stress concentration factors for concrete-filled steel tubular K-joints A systematic review of digital twins for electric vehicles Architecture, application, and prospect of digital twin for highway infrastructure Assessing the risk of pedestrian crossing behavior on suburban roads using structural equation model
×
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