Improved Sine Cosine Algorithm for searching global optima

SCA is the most successful population-based meta-heuristic algorithm commonly used to achieve global optimal value. The purpose of this paper is to study an improved version of the sine-cosine algorithm (ISCA) is tested on 13 standard functions and three technical problems like Welded Beam Design(WBD), compression spring design(CSD), pressure vessel design(PVD) and carried out results are compared with recent research articles of meta-heuristicalgorithms.A Wilcoxon rank sum test is performed to statistically validate the results.. The illustrated results prove that the better rendition of improved Sine Cosine Algorithm (ISCA) which indeed more capable to explore the search space, avoidance of local optima provide effective convergence for global optima and exploit search space for efficient optimization.