Evolutionary computation between Genetic Algorithm and Particle Swarm Optimization

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สุภกิจ นุตยะสกุล


- Genetic algorithm (GA) proved by many researchers that can solve optimization problems. However, GA lack on sharing information between the populations in consequent GA finds the solution quite slow. The new technique that is mentioned is particle swarm optimization (PSO). PSO is a technique in a group of evolutionary computation like GA. PSO find the best result by simulation moving of bird or fish to find foods or living, unlike GA. The GA uses the candidate of population to find the solution. This article presents techniques of PSO comparing with GA to point out the difference the process finding the solution.

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How to Cite
นุตยะสกุล ส., “Evolutionary computation between Genetic Algorithm and Particle Swarm Optimization”, JIST, vol. 2, no. 2, pp. 13–22, Dec. 2011.
Research Article: Soft Computing (Detail in Scope of Journal)


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