研究模糊信息下的车辆调度问题

Lu Lin
{"title":"研究模糊信息下的车辆调度问题","authors":"Lu Lin","doi":"10.1109/ICSSSM.2009.5174874","DOIUrl":null,"url":null,"abstract":"To solve the vehicle scheduling sever problem under fuzzy information, the paper takes vehicle's fuzzy travel time and customer's fuzzy due time as fuzzy information parameter and uses the method of subdividing the customer's class to absorb the carriers' knowledge system, builds two deciding-making goals of logistic enterprises' utility maximization and customers' s utility maximization to two kinds of fuzzy information dynamic vehicle scheduling model, and proposes ant colony optimization method to solve this problem. The artificial test analyzes the influence of the computed results of these two kinds of models with the change of policy-making parameters and suggests the frame basis of correlation parameters of the formulation.","PeriodicalId":287881,"journal":{"name":"2009 6th International Conference on Service Systems and Service Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study vehicle scheduling sever problem under fuzzy information\",\"authors\":\"Lu Lin\",\"doi\":\"10.1109/ICSSSM.2009.5174874\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the vehicle scheduling sever problem under fuzzy information, the paper takes vehicle's fuzzy travel time and customer's fuzzy due time as fuzzy information parameter and uses the method of subdividing the customer's class to absorb the carriers' knowledge system, builds two deciding-making goals of logistic enterprises' utility maximization and customers' s utility maximization to two kinds of fuzzy information dynamic vehicle scheduling model, and proposes ant colony optimization method to solve this problem. The artificial test analyzes the influence of the computed results of these two kinds of models with the change of policy-making parameters and suggests the frame basis of correlation parameters of the formulation.\",\"PeriodicalId\":287881,\"journal\":{\"name\":\"2009 6th International Conference on Service Systems and Service Management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 6th International Conference on Service Systems and Service Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSSM.2009.5174874\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 6th International Conference on Service Systems and Service Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2009.5174874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为解决模糊信息下的车辆调度问题,以车辆的模糊行程时间和顾客的模糊到期时间为模糊信息参数,采用细分顾客类别的方法吸收承运人的知识系统,建立了物流企业效用最大化和顾客效用最大化两个决策目标的两种模糊信息动态车辆调度模型。并提出了蚁群优化方法来解决这一问题。人工试验分析了两种模型计算结果随决策参数变化的影响,提出了公式相关参数的框架基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study vehicle scheduling sever problem under fuzzy information
To solve the vehicle scheduling sever problem under fuzzy information, the paper takes vehicle's fuzzy travel time and customer's fuzzy due time as fuzzy information parameter and uses the method of subdividing the customer's class to absorb the carriers' knowledge system, builds two deciding-making goals of logistic enterprises' utility maximization and customers' s utility maximization to two kinds of fuzzy information dynamic vehicle scheduling model, and proposes ant colony optimization method to solve this problem. The artificial test analyzes the influence of the computed results of these two kinds of models with the change of policy-making parameters and suggests the frame basis of correlation parameters of the formulation.
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:481959085
Book学术官方微信