{"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}
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.