Abstract:

An Adaptive differential evolution Artificial Bee Colony (ABC) algorithm based on segmental-search strategy is proposed, in order to overcome the problems of good exploration but poor at exploitation and poor convergence of conventional algorithm when using ABC algorithm to solve function optimization. In this algorithm, the mutation in differential evolution algorithm is introduced into the local search process of onlooker bees, and then, onlooker bees could do the local search around the current optimal solution which after employed bees dimension variation, and segmental-search strategy is used to improve the updating rate of food sources, which aims to improve the local search capability of the algorithm. Simulation results of six classic functions show that compared with the basic ABC algorithm, the modified ABC algorithm effectively balances the exploration and exploitation, and greatly improves the accuracy of solution and convergence rate.

Key words: Artificial Bee Colony (ABC), segmental-search, differential evolution, current optimal solution