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Taymaz Rahkar-Farshi

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Taymaz Rahkar-Farshi

WSEAS Transactions on Computers

Print ISSN: 1109-2750
E-ISSN: 2224-2872

Volume 17, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

A Multimodal Firefly Optimization Algorithm Based on Coulomb’s Law

AUTHORS: Taymaz Rahkar-Farshi

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ABSTRACT: In this paper, a multimodal firefly algorithm named the CFA (Coulomb Firefly Algorithm) has been presented based on the Coulomb’s law. The algorithm is able to find more than one optimum solution in the problem search space without requiring any additional parameter. In this proposed method, less bright fireflies would be attracted to fireflies which are not only brighter, but according to the Coulomb’s law pose the highest gravity. Approaching the end of iteration, fireflies' motion steps are reduced which finally results in a more accurate result. With limited number of iterations, groups of fireflies gather around global and local optimal points. After the final iteration, the firefly which has the highest fitness value, would be survived and the rest would be omitted. Experiments and comparisons on the CFA algorithm show that the proposed method has successfully reacted in solving multimodal optimization problems.

KEYWORDS: Swarm Intelligence, multimodal firefly algorithm, multimodal optimization, firefly algorithm


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WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 17, 2018, Art. #6, pp. 52-61

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