Comparative Study of Particle Swarm Optimization and Genetic Algorithms for Complex Mathematical Functions

• Autorzy: Valdez F. , Melin P.
• Języki publikacji: EN

Abstrakty

EN

The Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA) have been used successfully in solving problems of optimization with continuous and combinatorial search spaces. In this paper the results of the application of PSO and GAs for the optimization of mathematical functions are presented. These two methodologies have been implemented with the goal of making a comparison of their performance in solving complex optimization problems. This paper describes a comparison between a GA and PSO for the optimization of complex mathematical functions.

Słowa kluczowe

EN

genetic algorithms; particle swarm optimization (PSO); hybrid systems; optimization

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2008
• Tom: Vol. 2, No. 1
• Strony: 43--51
• Opis fizyczny: Bibliogr. 14 poz., rys.

Twórcy

autor

Valdez F.

autor

Melin P.

• PhD Student of Computer Science in the Universidad Autonoma de Baja California, Tijuana, B. C., Mexico,

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