Sine–cosine crow search algorithm: theory and applications - Khalilpourazari, Soheyl; Pasandideh, Seyed Hamid Reza (Neural computing & applications, 2020)
In this paper, we propose a new hybrid algorithm called sine–cosine crow search algorithm that inherits advantages of two recently developed algorithms, including crow search algorithm (CSA) and sine–cosine algorithm (SCA). The exploration and exploitation capabilities of the proposed algorithm have significantly improved. Performance of the so-called SCCSA was evaluated in unimodal, multimodal, fixed-dimensional multimodal and composite benchmark functions using robust measures. Based on in-depth analyses and statistical information, we showed that the suggested methodology could provide promising solutions comparing to other state-of-the-art algorithms.