Abstract
Evacuation route planning is one of the most crucial tasks for solving massive evacuation problem. In large public places, pedestrians should be transferred to safe areas when nature or man-made accidents happen. A multi-objective ant colony algorithm for massive pedestrian evacuation is presented in this paper. In the algorithm, three objectives, total evacuation time of all evacuees, total routes risk degree and total crowding degree are minimized simultaneously. Ants search routes and converge toward the Pareto optimal solutions in the light of the pheromone. The experimental results show that the approach is efficient and effective to solve massive evacuation problem with rapid, reasonable and safe plans.
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Zong, X., Xiong, S., Fang, Z., Li, Q. (2010). Multi-Objective Optimization for Massive Pedestrian Evacuation Using Ant Colony Algorithm. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13495-1_78
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DOI: https://doi.org/10.1007/978-3-642-13495-1_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13494-4
Online ISBN: 978-3-642-13495-1
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