Title :
Multi-objective optimization model based on heuristic ant colony algorithm for emergency evacuation
Author :
Duan, Pengfei ; Xiong, Shengwu ; Jiang, Hongxin
Author_Institution :
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China
Abstract :
It is important to evacuate pedestrians properly in large public buildings under emergency conditions. A multi-objective optimization model based on heuristic ant colony algorithm for emergency evacuation is proposed in this paper. The two objectives of this model are to minimize the evacuation clearance time and to minimize the total path crowding degree. The heuristic ant colony algorithm takes into account the distances between the evacuees and the dangerous or safe targets. In addition, this model is applied to a large stadium to simulate the whole evacuation process. In order to prove the results realistic, experiments that consider the evacuees´ real responses to the instructions are conducted. By simulating the process of pedestrian evacuation with this model, the results show the feasibility of the algorithm, so as to provide a scientific basis for guiding the real evacuation process.
Keywords :
ant colony optimisation; emergency services; minimisation; emergency evacuation; evacuation clearance time minimization; heuristic ant colony algorithm; multiobjective optimization model; pedestrian evacuation process simulation; total path crowding degree minimization; Architecture; Buildings; Computational modeling; Computer science; Educational institutions; Heuristic algorithms; Optimization;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4673-3064-0
Electronic_ISBN :
2153-0009
DOI :
10.1109/ITSC.2012.6338611