Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4633643 | Applied Mathematics and Computation | 2009 | 25 Pages |
Abstract
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.
Keywords
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Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Dervis Karaboga, Bahriye Akay,