An improved artificial bee colony algorithm

The Artificial Bee Colony (ABC) algorithm is a new swarm optimization algorithm with good numerical optimization results. This paper presents an improved algorithm called fast mutation artificial bee colony algorithm or FMABC. During choosing food sources, the onlookers use the pheromone and the sensitivity model in Free Search algorithm to replace the traditional roulette wheel selection model. Then, a mutation strategy based on opposition-based learning was proposed instead of the behavior of scouts. Application of this improved ABC algorithm on seven benchmark optimization functions shows a marked improvement in performance over the traditional ABC.