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  • 标题:Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO
  • 本地全文:下载
  • 作者:Jialiang Kou ; Shengwu Xiong ; Zhixiang Fang
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2013
  • 卷号:2013
  • DOI:10.1155/2013/369016
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Multiobjective evacuation routes optimization problem is defined to find out optimal evacuation routes for a group of evacuees under multiple evacuation objectives. For improving the evacuation efficiency, we abstracted the evacuation zone as a superposed potential field network (SPFN), and we presented SPFN-based ACO algorithm (SPFN-ACO) to solve this problem based on the proposed model. In Wuhan Sports Center case, we compared SPFN-ACO algorithm with HMERP-ACO algorithm and traditional ACO algorithm under three evacuation objectives, namely, total evacuation time, total evacuation route length, and cumulative congestion degree. The experimental results show that SPFN-ACO algorithm has a better performance while comparing with HMERP-ACO algorithm and traditional ACO algorithm for solving multi-objective evacuation routes optimization problem.
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