A comparative study of Artificial Bee Colony algorithm |
| |
Authors: | Dervis Karaboga Bahriye Akay |
| |
Institution: | Erciyes University, The Department of Computer Engineering, Melikgazi, 38039 Kayseri, Turkey |
| |
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: | Swarm intelligence Evolution strategies Genetic algorithms Differential evolution Particle swarm optimization Artificial Bee Colony algorithm Unconstrained optimization |
本文献已被 ScienceDirect 等数据库收录! |