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.
Comparison between GA and PSO in Analyzing Pavement Management Activities
Journal of Transportation Engineering ; 140 , 1 ; 99-104
13.06.2013
62014-01-01 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Comparison between GA and PSO in Analyzing Pavement Management Activities
Online Contents | 2014
|Comparison between GA and PSO in Analyzing Pavement Management Activities
British Library Online Contents | 2014
|Pavement management activities
TIBKAT | 1984
|Analysis of Pavement Management Activities Programming by Genetic Algorithms
Online Contents | 1998
|