Journal
STUDIES IN INFORMATICS AND CONTROL
Volume 21, Issue 2, Pages 137-146Publisher
NATL INST R&D INFORMATICS-ICI
DOI: 10.24846/v21i2y201203
Keywords
Artificial bee colony (ABC); Constrained optimization; Swarm intelligence; Nature inspired metaheuristics
Funding
- Ministry of Education and Science of Republic of Serbia [III-44006]
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Artificial bee colony (ABC) is a relatively new swarm intelligence based metaheuristic. It was successfully applied to unconstrained optimization problems and later it was adjusted for constrained problems as well. In this paper we introduce modifications to the ABC algorithm for constrained optimization problems that improve performance of the algorithm. Modifications are based on genetic algorithm (GA) operators and are applied to the creation of new candidate solutions. We implemented our modified algorithm and tested it on 13 standard benchmark functions. The results were compared to the results of the latest (2011) Karaboga and Akay's ABC algorithm and other state-of-the-art algorithms where our modified algorithm showed improved performance considering best solutions and even more considering mean solutions.
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