A comparative study of Artificial Bee Colony algorithm

KARABOĞA D., AKAY B.

APPLIED MATHEMATICS AND COMPUTATION, cilt.214, sa.1, ss.108-132, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 214 Sayı: 1
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.amc.2009.03.090
  • Dergi Adı: APPLIED MATHEMATICS AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.108-132
  • Anahtar Kelimeler: Swarm intelligence, Evolution strategies, Genetic algorithms, Differential evolution, Particle swarm optimization, Artificial Bee Colony algorithm, Unconstrained optimization, ABC OPTIMIZATION ALGORITHM, EVOLUTION
  • Erciyes Üniversitesi Adresli: Evet

Özet

Artificial Bee Colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms. ABC simulates the intelligent foraging behaviour of a honeybee swarm. In this work, ABC is used for optimizing a large set of numerical test functions and the results produced by ABC algorithm are compared with the results obtained by genetic algorithm, particle swarm optimization algorithm, differential evolution algorithm and evolution strategies. Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters. (C) 2009 Elsevier Inc. All rights reserved.