Optimization of Benchmark Functions Using Artificial Bee Colony (ABC) Algorithm
نویسندگان
چکیده
The Artificial Bee Colony (ABC) algorithm is one of most popular stochastic, swarm based algorithm proposed by Karaboga in 2005 inspired from the foraging behaviour of honey bees. ABC has been applied to solve several problems in various fields and also many researchers have attempted to improve ABC’s performance by making some modifications. This paper proposes a new variant of ABC algorithm based on rectangular topology structure, namely rectangular topology based Artificial Bee Colony algorithm (RABC). RABC significantly improves the original ABC in solving high dimensional optimization problems. In this work, RABC algorithm is tested on a set of five benchmark functions. The performance of RABC algorithm is compared with original ABC. The simulation results show that the proposed RABC outperforms the original ABC in terms of convergence, robustness and solution quality.
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