A new hybrid optimization method combining artificial bee colony and limited-memory BFGS algorithms for efficient numerical optimization

Badem H., BAŞTÜRK A., Caliskan A., YÜKSEL M. E.

APPLIED SOFT COMPUTING, cilt.70, ss.826-844, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 70
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.asoc.2018.06.010
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.826-844
  • Anahtar Kelimeler: Artificial bee colony algorithm, L-BEGS, Global optimization, Swarm intelligence, SEARCH, PERFORMANCE
  • Erciyes Üniversitesi Adresli: Evet

Özet

In this paper, a new optimization method, which is developed especially for optimization of functions with a large number of local minima, is presented. The proposed method is a hybrid optimization algorithm which employs the artificial bee colony (ABC) and limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithms for combining their powerful features. The most prominent feature of the proposed method over other methods is that it provides accurate results and valuable convergence speeds, as well as easy implementation at the same time. Extensive simulation results supported by detailed statistical analyses show that the proposed method can be used for efficient optimization of functions including well-known benchmark functions and CEC2016 competition functions. (C) 2018 Elsevier B.V. All rights reserved.