Adaptive Constriction Factor for Location-related Particle Swarm
نویسندگان
چکیده
-Particle Swarm Optimization (PSO) has received increased attention in the evolutionary computation fields recently. In the paper, we proposed Adaptive constriction factor for Location-related Particle Swarm (ALPS) that is shown to be superior when compared with the existing PSO algorithm. We adapt a technique of overcoming complex problems with PSO. This is accomplished by using the ratio of the relative location of better particles to determine the direction in which each constriction factor of the particle needs to be varied. Finally, we are presented experiment results on benchmark functions testify ALPS’s efficiency. Key-Words: Particle swarm optimization, optimization, evolutionary computation, constriction factor, adaptive method.
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