A Multimodal Firefly Optimization Algorithm Based on Coulomb's Law

Rahkar-Farshi T., Behjat-Jamal S.

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, cilt.7, sa.5, ss.134-141, 2016 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 5
  • Basım Tarihi: 2016
  • Dergi Adı: INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Index Islamicus, INSPEC
  • Sayfa Sayıları: ss.134-141
  • Anahtar Kelimeler: Swarm Intelligence, multimodal firefly algorithm, multimodal optimization, firefly algorithm, NICHING GENETIC ALGORITHM, REPLACEMENT
  • Gazi Üniversitesi Adresli: Evet

Özet

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.