An improved artificial bee colony algorithm with fast strategy, and its application

In recent years, artificial bee colonies (ABC) have yielded favorable results from among other evolutionary algorithms. In spite of its strong global presence, how to accelerate ABC's convergence is an important factor that contributes toward improving its performance. In this paper, the proposed updating equation of onlooker bees employs two alternatives which are selected based upon whether the achievement of the updated bee is better than that of the generated individual. A Cauchy operator is employed to balance the global and local search capabilities of individuals. Various common benchmark functions and a real world problem are employed to verify the effectiveness of our algorithm by comparing these with some modern ABC variants.