自然灾害情况下考虑二次库配置的改进反应性禁忌搜索优化车辆路径

Sara Onoda, Y. Fukuyama
{"title":"自然灾害情况下考虑二次库配置的改进反应性禁忌搜索优化车辆路径","authors":"Sara Onoda, Y. Fukuyama","doi":"10.1109/SA51175.2021.9507126","DOIUrl":null,"url":null,"abstract":"This paper proposes improved reactive tabu search for optimal vehicle routing of vehicles considering allocation of secondary depots in case of natural disasters. In recent years, many large-scale disasters have occurred in Japan and large-scale disasters may occur in the near future, unfortunately. In case of large-scale disasters, emergency relief supply logistics is an important issue since it will affect lives of evacuees. The proposed method modifies a stored method of a tabu list, introduces aspiration criteria, and applies a searched list using a hash function for simultaneously solving the optimal number of secondary depots, the optimal placement and the distribution areas of secondary depots, and the optimal routes of vehicles in the distribution area of secondary depots. It is verified that the proposed method can generate higher quality optimal vehicle routing and reduce computation time than the conventional reactive tabu search based method with actual evacuation facility data of Chiba City, which are planned to be used in case of natural disasters. The results are confirmed by Wilcoxon test.","PeriodicalId":117020,"journal":{"name":"2020 2nd International Conference on Societal Automation (SA)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved Reactive Tabu Search for Optimal VehicleRouting Considering Allocation of Secondary Depots in Case of Natural Disasters\",\"authors\":\"Sara Onoda, Y. Fukuyama\",\"doi\":\"10.1109/SA51175.2021.9507126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes improved reactive tabu search for optimal vehicle routing of vehicles considering allocation of secondary depots in case of natural disasters. In recent years, many large-scale disasters have occurred in Japan and large-scale disasters may occur in the near future, unfortunately. In case of large-scale disasters, emergency relief supply logistics is an important issue since it will affect lives of evacuees. The proposed method modifies a stored method of a tabu list, introduces aspiration criteria, and applies a searched list using a hash function for simultaneously solving the optimal number of secondary depots, the optimal placement and the distribution areas of secondary depots, and the optimal routes of vehicles in the distribution area of secondary depots. It is verified that the proposed method can generate higher quality optimal vehicle routing and reduce computation time than the conventional reactive tabu search based method with actual evacuation facility data of Chiba City, which are planned to be used in case of natural disasters. The results are confirmed by Wilcoxon test.\",\"PeriodicalId\":117020,\"journal\":{\"name\":\"2020 2nd International Conference on Societal Automation (SA)\",\"volume\":\"205 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Conference on Societal Automation (SA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SA51175.2021.9507126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Societal Automation (SA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SA51175.2021.9507126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

针对自然灾害情况下考虑二次库配置的车辆路径优化问题,提出了改进的反应性禁忌搜索算法。近年来,日本发生了许多大规模灾害,不幸的是,不久的将来可能会发生大规模灾害。在发生大规模灾害的情况下,紧急救援物资的物流是一个重要的问题,因为它会影响到被疏散者的生活。该方法改进了禁忌列表的存储方法,引入了期望准则,并采用哈希函数的搜索列表同时求解二次库的最优数量、二次库的最优布局和分布区域,以及车辆在二次库分布区域的最优路径。利用千叶市疏散设施的实际数据,验证了该方法比传统的基于反应性禁忌搜索的方法能够生成质量更高的最优车辆路径,并减少了计算时间。结果经Wilcoxon试验证实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Reactive Tabu Search for Optimal VehicleRouting Considering Allocation of Secondary Depots in Case of Natural Disasters
This paper proposes improved reactive tabu search for optimal vehicle routing of vehicles considering allocation of secondary depots in case of natural disasters. In recent years, many large-scale disasters have occurred in Japan and large-scale disasters may occur in the near future, unfortunately. In case of large-scale disasters, emergency relief supply logistics is an important issue since it will affect lives of evacuees. The proposed method modifies a stored method of a tabu list, introduces aspiration criteria, and applies a searched list using a hash function for simultaneously solving the optimal number of secondary depots, the optimal placement and the distribution areas of secondary depots, and the optimal routes of vehicles in the distribution area of secondary depots. It is verified that the proposed method can generate higher quality optimal vehicle routing and reduce computation time than the conventional reactive tabu search based method with actual evacuation facility data of Chiba City, which are planned to be used in case of natural disasters. The results are confirmed by Wilcoxon test.
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
自引率
0.00%
发文量
0
×
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:604180095
Book学术官方微信