On the hybridization of the artificial Bee Colony and Particle Swarm Optimization Algorithms

• Autorzy: El-Abd M.
• Języki publikacji: EN

Abstrakty

EN

In this paper we investigate the hybridization of two swarm intelligence algorithms; namely, the Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO). The hybridization technique is a component-based one, where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. Three different versions of the hybrid algorithm are tested in this work by experimenting with different selection mechanisms for the ABC component. All the algorithms are applied to the well-known CEC05 benchmark functions and compared based on three different metrics, namely, the solution reached, the success rate, and the performance rate.

Słowa kluczowe

EN

Artificial Bee Colony Algorithm; ABC; particle swarm optimization (PSO); PSO; hybridization; hybrid algorithm; CEC05

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2012
• Tom: Vol. 2, No. 2
• Strony: 147--155
• Opis fizyczny: Bibliogr. 15 poz., rys.

Twórcy

autor

El-Abd M.

• Computer Engineering, American University of Kuwait, Kuwait

Bibliografia

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