By Topic

Multi-objective optimization model based on heuristic ant colony algorithm for emergency evacuation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Pengfei Duan ; Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China ; Shengwu Xiong ; Hongxin Jiang

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.

Published in:

Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on

Date of Conference:

16-19 Sept. 2012