A cooperative learning artificial bee colony algorithm with multiple search mechanisms

Article type: Research Article

Authors: Harfouchi, Fatima^* | Habbi, Hacene

Affiliations: Applied Automation Laboratory, M'hamed Bougara University of Boumerdès, Boumerdès, Algeria

Correspondence: [*] Corresponding author: Fatima Harfouchi, Applied Automation Laboratory, M'hamed Bougara University of Boumerdès, Avenue de l'indépendance 35000 Boumerdès, Algeria. E-mail:[email protected]

Abstract: Improving Artificial Bee Colony (ABC) optimization concept and performance is still devoting substantial interest. Enhancements are usually introduced in order to deal with some challenging issues such as exploitation and exploration abilities that have important impact on the convergence of the algorithm. Balancing these two properties can be achieved by manipulating the search strategies but also the general framework of the ABC model. This work along this idea develops a novel multiple search ABC with a cooperative learning paradigm, referred to as CLABC (Cooperative Learning ABC) algorithm. The attempt is to build a novel algorithmic framework relying on a better characterization of social learning capability among swarm bees with incorporating behavioral differences. The proposed approach is tested on several benchmark functions and compared with other ABC variants and advanced metaheuristics. The performance of the proposed CLABC can be clearly deduced from the obtained results that show superiority in the most of test cases.

Keywords: Artificial bee colony (ABC) algorithm, cooperative learning, search mechanism, swarm intelligence

DOI: 10.3233/HIS-160229

Journal: International Journal of Hybrid Intelligent Systems, vol. 13, no. 2, pp. 113-124, 2016