Title :
Evacuation Planning via Evolutionary Computation
Author :
Garrett, A. ; Muhdi, R. ; Davis, J. ; Dozier, Gerry ; SanSoucie, M.P. ; Hull, P.V. ; Tinker, M.L.
Author_Institution :
Department of Computer Science and Software Engineering, ACI Lab, Auburn University, Auburn, AL
Abstract :
According to the Life Safety Codereg, the geometry of a building, the location of exits, and the number of exits dictate the means of egress for all people occupying a building. In this paper we show how evolutionary computations in the form of Genetic Algorithms and Estimation of Distribution Algorithms are used to evolve the placement of exits in order to optimize overall evacuation time. In particular, a generational GA, a steady-state GA, and an elitist EDA are used to evolve the placement of exits for two practical design problems. The algorithms are evaluated in terms of success rate, number of function evaluations, and best fitness. For both problems, the steady-state GA outperformed the other algorithms in all evaluation categories.
Keywords :
evolutionary computation; genetic algorithms; building geometry; distribution estimation algorithms; egress; evacuation planning; evolutionary computation; exits; genetic algorithms; Buildings; Electronic design automation and methodology; Evolutionary computation; Fires; Genetic algorithms; Geometry; Humans; NASA; Safety; Steady-state;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688303