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Computational Intelligence and Neuroscience
Volume 2013 (2013), Article ID 369016, 11 pages
Research Article

Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO

1School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China
2State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
3School of Computer Science and Technology, Hubei University of Technology, Wuhan 430068, China

Received 21 March 2013; Revised 16 May 2013; Accepted 21 May 2013

Academic Editor: Cheng-Jian Lin

Copyright © 2013 Jialiang Kou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.