Comparison between GA and PSO in Analyzing Pavement Management Activities
Publication: Journal of Transportation Engineering
Volume 140, Issue 1
Abstract
This paper demonstrates the application of particle swarm optimization (PSO) to the programming of pavement maintenance activities at the network level. Furthermore, the application of the PSO technique and its relevance to solving the programming problem in a pavement management system (PMS) is discussed. The robustness and quick search capability of PSO enables it to effectively handle the highly constrained problem of pavement management activities programming, which has an extremely large solution space of astronomical scale. Examples are presented to highlight the versatility of PSO in accommodating different forms of objective functions and comparing the results with the genetic algorithm (GA). This paper compares PSO and GA with respect to rate of convergence and accuracy of modeling PMS using an example problem. The results of this paper confirmed the potential of PSO to successfully model the PMS.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 140 • Issue 1 • January 2014
Pages: 99 - 104
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Jun 16, 2011
Accepted: Jun 11, 2013
Published online: Jun 13, 2013
Discussion open until: Nov 13, 2013
Published in print: Jan 1, 2014
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