A novel Artificial Bee Colony algorithm with integration of extremal optimization for numerical optimization problems
Min-Rong Chen, Wei Zeng, Guo‐Qiang Zeng, Xia Li, Jianping Luo · 2014
Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on a particular intelligent behaviour of honeybee swarms. The standard ABC is weak at the local-search capability and precision. Extremal Optimization (EO) is a general-purpose heuristic method which has strong local-search capability and has been successfully applied to a wide variety of hard optimization problems. In order to strengthen the local-search capability of ABC, this work proposes a novel hybrid optimization method, called ABC-EO algorithm, through introducing EO to ABC. The simulation results show that the performance of the proposed method is as good as or superior to those of the state-of-the-art algorithms in complex numerical optimization problems.