A New Hybrid Algorithm for Multiobjective Optimization

Abstract

Hybridization of intelligent techniques, coming from different computational intelligence areas, has become popular because of the growing awareness that such combinations frequently perform better than the individual techniques coming from computational intelligence. Therefore, in this paper a combined model based on honey bees mating optimization and Extremal Optimization has been developed. So it can converge to optimum points faster than before. Simulation and comparisons based on several well-studied and new benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed algorithms.