面向可持续性的路线生成,用于拼车服务

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Mengya Liu, Vahid Yazdanpanah, Sebastian Stein, Enrico Gerding
{"title":"面向可持续性的路线生成,用于拼车服务","authors":"Mengya Liu, Vahid Yazdanpanah, Sebastian Stein, Enrico Gerding","doi":"10.2298/csis221209053l","DOIUrl":null,"url":null,"abstract":"Sustainability is the ability to maintain and preserve natural and man made systems for the benefit of current and future generations. The three pillars of sustainability are social, economic, and environmental. These pillars are interdependent and interconnected, meaning that progress in one area can have positive or negative impacts on the others. This calls for smart methods to balance such benefits and find solutions that are optimal with respect to all the three pillars of sustainability. By using AI methods, in particular, genetic algorithms for multiobjective optimisation, we can better understand and manage complex systems in order to achieve sustainability. In the context of sustainability-oriented ridesharing, genetic algorithms can be used to optimise route finding in order to lower the cost of trans portation and reduce emissions. This work contributes to this domain by using AI, specifically genetic algorithms for multiobjective optimisation, to improve the efficiency and sustainability of transportation systems. By using this approach, we can make progress towards achieving the goals of the three pillars of sustainability.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sustainability-oriented route generation for ridesharing services\",\"authors\":\"Mengya Liu, Vahid Yazdanpanah, Sebastian Stein, Enrico Gerding\",\"doi\":\"10.2298/csis221209053l\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sustainability is the ability to maintain and preserve natural and man made systems for the benefit of current and future generations. The three pillars of sustainability are social, economic, and environmental. These pillars are interdependent and interconnected, meaning that progress in one area can have positive or negative impacts on the others. This calls for smart methods to balance such benefits and find solutions that are optimal with respect to all the three pillars of sustainability. By using AI methods, in particular, genetic algorithms for multiobjective optimisation, we can better understand and manage complex systems in order to achieve sustainability. In the context of sustainability-oriented ridesharing, genetic algorithms can be used to optimise route finding in order to lower the cost of trans portation and reduce emissions. This work contributes to this domain by using AI, specifically genetic algorithms for multiobjective optimisation, to improve the efficiency and sustainability of transportation systems. By using this approach, we can make progress towards achieving the goals of the three pillars of sustainability.\",\"PeriodicalId\":50636,\"journal\":{\"name\":\"Computer Science and Information Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science and Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2298/csis221209053l\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science and Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2298/csis221209053l","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

可持续性是为了当代人和子孙后代的利益而维持和保护自然和人为系统的能力。可持续发展的三大支柱是社会、经济和环境。这些支柱是相互依存和相互联系的,这意味着一个领域的进展可能对其他领域产生积极或消极的影响。这需要明智的方法来平衡这些好处,并找到关于可持续性的所有三个支柱的最佳解决方案。通过使用人工智能方法,特别是用于多目标优化的遗传算法,我们可以更好地理解和管理复杂系统,以实现可持续性。在以可持续发展为导向的拼车环境中,遗传算法可用于优化寻路,以降低运输成本并减少排放。这项工作通过使用人工智能,特别是用于多目标优化的遗传算法,来提高交通系统的效率和可持续性,从而为这一领域做出贡献。通过使用这种方法,我们可以在实现可持续性三大支柱的目标方面取得进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sustainability-oriented route generation for ridesharing services
Sustainability is the ability to maintain and preserve natural and man made systems for the benefit of current and future generations. The three pillars of sustainability are social, economic, and environmental. These pillars are interdependent and interconnected, meaning that progress in one area can have positive or negative impacts on the others. This calls for smart methods to balance such benefits and find solutions that are optimal with respect to all the three pillars of sustainability. By using AI methods, in particular, genetic algorithms for multiobjective optimisation, we can better understand and manage complex systems in order to achieve sustainability. In the context of sustainability-oriented ridesharing, genetic algorithms can be used to optimise route finding in order to lower the cost of trans portation and reduce emissions. This work contributes to this domain by using AI, specifically genetic algorithms for multiobjective optimisation, to improve the efficiency and sustainability of transportation systems. By using this approach, we can make progress towards achieving the goals of the three pillars of sustainability.
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
Computer Science and Information Systems
Computer Science and Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
2.30
自引率
21.40%
发文量
76
审稿时长
7.5 months
期刊介绍: About the journal Home page Contact information Aims and scope Indexing information Editorial policies ComSIS consortium Journal boards Managing board For authors Information for contributors Paper submission Article submission through OJS Copyright transfer form Download section For readers Forthcoming articles Current issue Archive Subscription For reviewers View and review submissions News Journal''s Facebook page Call for special issue New issue notification Aims and scope Computer Science and Information Systems (ComSIS) is an international refereed journal, published in Serbia. The objective of ComSIS is to communicate important research and development results in the areas of computer science, software engineering, and information systems.
×
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