{"title":"Feasible Route Determination Using Ant Colony Optimization in Evacuation Planning","authors":"Arief Rahman, Ahmad Kamil Mahmood","doi":"10.1109/SCORED.2007.4451424","DOIUrl":null,"url":null,"abstract":"The most complex aspect of people movement on emergency condition is how to select the shortest way out from multi exit ways in the multi-floors building. The purpose of this paper is to demonstrate how an ant colony optimization (ACO) can be used in evacuation planning. Modified ACO applied as the algorithm to determine the feasible route during emergency evacuation. Physical obstacle during building evacuation such as bottleneck or disaster problem has been considered in transitional probability rule of ACO. By creating exit sign (an agent) with ACO as the algorithm, this agent decides the feasible route and guides the occupant during the evacuation. Two scenarios present to observe the performance of two different approaches in making decision during evacuation. When the obstacle appeared, route selection based on ACO algorithm has faster total evacuation time significantly than familiarity of environment exit method.","PeriodicalId":443652,"journal":{"name":"2007 5th Student Conference on Research and Development","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 5th Student Conference on Research and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCORED.2007.4451424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The most complex aspect of people movement on emergency condition is how to select the shortest way out from multi exit ways in the multi-floors building. The purpose of this paper is to demonstrate how an ant colony optimization (ACO) can be used in evacuation planning. Modified ACO applied as the algorithm to determine the feasible route during emergency evacuation. Physical obstacle during building evacuation such as bottleneck or disaster problem has been considered in transitional probability rule of ACO. By creating exit sign (an agent) with ACO as the algorithm, this agent decides the feasible route and guides the occupant during the evacuation. Two scenarios present to observe the performance of two different approaches in making decision during evacuation. When the obstacle appeared, route selection based on ACO algorithm has faster total evacuation time significantly than familiarity of environment exit method.