Improved Cuckoo Search with Better Search Capabilities for Solving CEC2017 Benchmark Problems

Cuckoo Search is a nature inspired evolutionary algorithm to solve real-world optimization problems. It is inspired from the brood parasitism of cuckoos. It is highly competitive and has been used to solve number of problems in the field of science and engineering. A number of modifications have been proposed to enhance its performance in the past. This paper presents an improved version of CS namely CVnew in which three modifications are proposed. The first modification is the introduction of two new search equations to improve the global search while the second one deals with the incorporation of four search equations to improve the local search. As a third modification, a balance between global and local search has been increased by exponentially decreasing the switch probability. The proposed algorithm has been applied to solve single objective real-parameter problems of CEC 2017. The numerical results prove the better performance of CVnew in comparison with SaDE, JADE, SHADE and MVMO.

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