PSO-Based Emergency Evacuation Simulation

The Emergency Evacuation Simulation (EES) has been increasingly becoming a hotspot in the field of transportation. PSO-based EES is a good choice as its low computation complexity compared with some other algorithms, especially in an emergency. The selection of fitness function of each particle in PSO is a key problem for EES. This paper will introduce some fitness functions for EES and present a new fitness function called Triple-Distance Safe Degree (TDSD). Through theoretical analysis and experimental validation, the TDSD is proved to be much better than other fitness functions introduced in this paper.

[1]  James Kennedy,et al.  Proceedings of the 1998 IEEE International Conference on Evolutionary Computation [Book Review] , 1999, IEEE Transactions on Evolutionary Computation.

[2]  Wang Cheng,et al.  A modified Particle Swarm Optimization-based human behavior modeling for emergency evacuation simulation system , 2008, 2008 International Conference on Information and Automation.

[3]  Liao Yanfen.  The Research of Evacuation Model in Urban Underground Business Buildings , 2008 .

[4]  Idel Montalvo,et al.  Forecasting pedestrian evacuation times by using swarm intelligence , 2009 .

[5]  Mark A. Turnquist,et al.  Lane-based evacuation network optimization: An integrated Lagrangian relaxation and tabu search approach , 2011 .

[6]  Richard L. Church,et al.  Mapping evacuation risk on transportation networks using a spatial optimization model , 2000 .

[7]  Marina Yusoff,et al.  An Improved Discrete Particle Swarm Optimization in Evacuation Planning , 2009, 2009 International Conference of Soft Computing and Pattern Recognition.

[8]  Ben Sheppard.  September 11 attacks , 2008 .

[9]  Li Lijun,et al.  A Multi-Agent and PSO Based Simulation for Human Behavior in Emergency Evacuation , 2007 .

[10]  Wang Cheng,et al.  A Multi-Agent and PSO Based Simulation for Human Behavior in Emergency Evacuation , 2007, 2007 International Conference on Computational Intelligence and Security (CIS 2007).

[11]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[12]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[13]  Kai Nagel,et al.  The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations , 2010 .

[14]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).