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Comparative Analysis of Particle Swarm Optimization and Particle Swarm Optimization with Aging Leader and Challengers towards Benchmark Functions
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 120 - Number 24 |
| Year of Publication: 2015 |
| Authors: Anu Sharma, Mandeep Kaur |
10.5120/21414-4457
|
Anu Sharma, Mandeep Kaur . Comparative Analysis of Particle Swarm Optimization and Particle Swarm Optimization with Aging Leader and Challengers towards Benchmark Functions. International Journal of Computer Applications. 120, 24 ( June 2015), 48-53. DOI=10.5120/21414-4457
Abstract
Particle swarm optimization is the populace based heuristic optimization technique motivated by swarm intelligence and aims to find the best solution in the swarm. Aging leader and challengers with Particle swarm optimization (ALC-PSO) is a PSO variant in which concept of leader and challenger is implanted ALC- PSO has been successful in preventing premature convergence problem of PSO. In this paper, we performed experimental analysis of the performance of ALC-PSO and Standard PSO Algorithm on different benchmark functions and made an effort to list out the performance differences between PSO and ALC-PSO.
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