A levy flight-based hybrid artificial bee colony algorithm for solving numerical optimization problems

Abstract

An artificial bee colony (ABC) algorithm is one of numerous swarm intelligence algorithms that employs the foraging behavior of honeybee colonies. To improve the convergence performance and search speed of finding the best solution using this approach, we propose a levy flight-based hybrid ABC algorithm in this paper. To evaluate the performance of the standard and proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation 2013 test suite. The proposed ABC algorithm demonstrated competitive performance on these optimization problems as compared to standard ABC, differential evolution, and particle swarm optimization algorithms with dimension sizes of 10, 30, and 50, respectively.