基于蚁群算法的多模式网络应急调度与路由双目标优化

Enze Liu, Junzhe Wang
{"title":"基于蚁群算法的多模式网络应急调度与路由双目标优化","authors":"Enze Liu, Junzhe Wang","doi":"10.1109/ICITE50838.2020.9231463","DOIUrl":null,"url":null,"abstract":"Traditionally, emergency passenger retention is evacuated by single-mode like by coach or railway. To reduce the passengers' delay that is closely related to personal time value and systematical fluence, the multi-mode traffic vehicles are supposed to dispatch economically and collaboratively. This study proposed a bi-objective optimization model, intending to minimize passenger delay and dispatching cost simultaneously, thereby obtaining the dispatching vehicle plan and the trip chain through the trade-off analysis. The Pareto solutions, including delay and expense, correspond to passengers allocating on a trip chain and the number of dispatched vehicles for each mode. A super network, combining coach, railway, high-speed train, and airplane subnetworks, is established to control the transfer times, transfer passenger volume, and multi-mode trip chain. The Ant Colony Optimization (ACO) is utilized, which has superiority on path selection on the network to solve the bi-criterion routing. The algorithm is improved in this research to search the optimal passenger evacuation path when the vehicle carriage capacity is uncertain. A case based on the Beijing-Tianjin-Hebei transportation integration shows the following: (1) The economic efficiency of adding spend is dropping on the Pareto front. (2) The reserved emergency vehicles are dispatched uniformly. (3) The railway is occupied mainly by short and medium distance passengers.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Bi-objective Optimization of Emergency Dispatching and Routing for Multi-mode Network Using Ant Colony Algorithm\",\"authors\":\"Enze Liu, Junzhe Wang\",\"doi\":\"10.1109/ICITE50838.2020.9231463\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditionally, emergency passenger retention is evacuated by single-mode like by coach or railway. To reduce the passengers' delay that is closely related to personal time value and systematical fluence, the multi-mode traffic vehicles are supposed to dispatch economically and collaboratively. This study proposed a bi-objective optimization model, intending to minimize passenger delay and dispatching cost simultaneously, thereby obtaining the dispatching vehicle plan and the trip chain through the trade-off analysis. The Pareto solutions, including delay and expense, correspond to passengers allocating on a trip chain and the number of dispatched vehicles for each mode. A super network, combining coach, railway, high-speed train, and airplane subnetworks, is established to control the transfer times, transfer passenger volume, and multi-mode trip chain. The Ant Colony Optimization (ACO) is utilized, which has superiority on path selection on the network to solve the bi-criterion routing. The algorithm is improved in this research to search the optimal passenger evacuation path when the vehicle carriage capacity is uncertain. A case based on the Beijing-Tianjin-Hebei transportation integration shows the following: (1) The economic efficiency of adding spend is dropping on the Pareto front. (2) The reserved emergency vehicles are dispatched uniformly. (3) The railway is occupied mainly by short and medium distance passengers.\",\"PeriodicalId\":112371,\"journal\":{\"name\":\"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITE50838.2020.9231463\",\"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 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITE50838.2020.9231463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

传统上,紧急滞留旅客疏散是采用单模方式,如长途汽车或铁路。为了减少与个人时间价值和系统影响密切相关的乘客延误,需要对多模式交通车辆进行经济协同调度。本研究提出了一个双目标优化模型,旨在同时使乘客延误和调度成本最小化,从而通过权衡分析得到调度车辆计划和行程链。帕累托解,包括延误和费用,对应于乘客分配在一个行程链和分配车辆的数量为每种模式。建立客车、铁路、高铁、飞机子网相结合的超级网络,控制换乘次数、换乘客流量、多模式出行链。利用蚁群算法在网络路径选择上的优势来解决双准则路由问题。本文对该算法进行了改进,在车辆承载能力不确定的情况下搜索最优乘客疏散路径。基于京津冀交通一体化的案例表明:(1)在帕累托前沿,增加支出的经济效率呈下降趋势。(2)统一调度预留应急车辆。(3)铁路以中短途旅客为主。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Bi-objective Optimization of Emergency Dispatching and Routing for Multi-mode Network Using Ant Colony Algorithm
Traditionally, emergency passenger retention is evacuated by single-mode like by coach or railway. To reduce the passengers' delay that is closely related to personal time value and systematical fluence, the multi-mode traffic vehicles are supposed to dispatch economically and collaboratively. This study proposed a bi-objective optimization model, intending to minimize passenger delay and dispatching cost simultaneously, thereby obtaining the dispatching vehicle plan and the trip chain through the trade-off analysis. The Pareto solutions, including delay and expense, correspond to passengers allocating on a trip chain and the number of dispatched vehicles for each mode. A super network, combining coach, railway, high-speed train, and airplane subnetworks, is established to control the transfer times, transfer passenger volume, and multi-mode trip chain. The Ant Colony Optimization (ACO) is utilized, which has superiority on path selection on the network to solve the bi-criterion routing. The algorithm is improved in this research to search the optimal passenger evacuation path when the vehicle carriage capacity is uncertain. A case based on the Beijing-Tianjin-Hebei transportation integration shows the following: (1) The economic efficiency of adding spend is dropping on the Pareto front. (2) The reserved emergency vehicles are dispatched uniformly. (3) The railway is occupied mainly by short and medium distance passengers.
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
期刊最新文献
Research on the Method and Application of Intelligent Information Service Demand Identification of Inland Waterway Research on Test Method of Commercial Vehicle Forward Collision Warning Systems An Optimized Multi-sensor Fused Object Detection Method for Intelligent Vehicles Research on Handling Equipment Allocation of Rail-Sea Intermodal Transportation in Container Terminals An Automatic Traffic Peak Picking Method Based on Max Tree
×
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