Reduction of artificial bee colony algorithm for global optimization

This paper presents a reduction of artificial bee colony algorithm for global optimization. Artificial bee colony algorithm is an optimization technique which refers to the behavior of honeybee swarms, and a multi-point search approach which finds a best solution using multiple bees. For avoiding local minima, a number of bees are initially prepared and their positions are updated by artificial bee colony algorithm. Bees sequentially reduce to reach a predetermined number of them grounded in the evaluation value and artificial bee colony algorithm continues until the termination condition is met. In order to show the effectiveness of the proposed algorithm, we examine the best value by using test functions compared to existing algorithms. Furthermore the influence of best value on the initial number of bees for our algorithm is discussed.