A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm
- DOI
- 10.2991/ijcis.d.200612.001How to use a DOI?
- Keywords
- Firefly algorithm; Artificial bee colony; Multi-strategy; Hybrid algorithm; Global optimization
- Abstract
Many hard optimization problems have been efficiently solved by two notable swarm intelligence algorithms, artificial bee colony (ABC) and firefly algorithm (FA). In this paper, a collaborative hybrid algorithm based on firefly and multi-strategy artificial bee colony, abbreviated as FA-MABC, is proposed for solving single-objective optimization problems. In the proposed algorithm, FA investigates the search space globally to locate favorable regions of convergence. A novel multi-strategy ABC is employed to perform local search. The proposed algorithm incorporates a diversity measure to help in the switch criteria. The FA-MABC is tested on 40 benchmark functions with diverse complexities. Comparative results with the basic FA, ABC and other recent state-of-the-art metaheuristic algorithms demonstrate the competitive performance of the FA-MABC.
- Copyright
- © 2020 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Download article (PDF)
View full text (HTML)
Cite this article
TY - JOUR AU - Ivona Brajević AU - Predrag S. Stanimirović AU - Shuai Li AU - Xinwei Cao PY - 2020 DA - 2020/06/23 TI - A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm JO - International Journal of Computational Intelligence Systems SP - 810 EP - 821 VL - 13 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.200612.001 DO - 10.2991/ijcis.d.200612.001 ID - Brajević2020 ER -