Improved Cuckoo Search Algorithm for Global Optimization

Abstract

The cuckoo search algorithm is a recently developed<br />meta-heuristic optimization algorithm, which is suitable for<br />solving optimization problems. To enhance the accuracy and<br />convergence rate of this algorithm, an improved cuckoo search<br />algorithm is proposed in this paper. Normally, the parameters<br />of the cuckoo search are kept constant. This may lead to<br />decreasing the efficiency of the algorithm. To cope with this<br />issue, a proper strategy for tuning the cuckoo search<br />parameters is presented. Considering several well-known<br />benchmark problems, numerical studies reveal that the<br />proposed algorithm can find better solutions in comparison<br />with the solutions obtained by the cuckoo search. Therefore, it<br />is anticipated that the improved cuckoo search algorithm can<br />successfully be applied to a wide range of optimization<br />problems.