Hybrid Gray Wolf Optimization and Cuckoo Search Algorithm based on the Taguchi Theory

A novel method was proposed which combines gray wolf optimizer (GWO) and cuckoo search algorithm (CS) based on the Taguchi theory in this paper. Generally speaking, the traditional GWO has a powerful ability to exploit locally and the traditional CS has a powerful ability to explore globally in the solution space. With the advantages of these two algorithms, a hybrid algorithm (GWO-CS) combined by the orthogonal array in Taguchi theory was developed. The Taguchi theory and its key method, orthogonal arrays, are widely used in the industrial field to improve the robustness of product design. The test results of the proposed algorithm (GWO-CS) with CEC2017 indicated its effectiveness compared with traditional and other homogeneous algorithms.