Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine cosine algorithm

Many real-life complex problems are formulated as optimization problems. These mathematical equations generally are non-convex and non-linear functions. These problems are effectively solved using nature inspired algorithms. Sine-cosine algorithm is one of the recent advancements in field of nature inspired optimization technique. Diversification and intensification are two components of a robust nature inspired algorithm. Sine-cosine algorithm has potential to solve many real-life complex problems. However, lack of diversification ability of search space leads to investigation of different mutation strategies-Gaussian, Cauchy, Random, Polynomial, Power mutation on sine-cosine algorithm. The scope of this paper is of three folds. Firstly, to purpose a new algorithm embedded with five different mutation strategies. Secondly, to check the proposed version of algorithm on 23 benchmark problems of efficient difficulty/complexity level. Thirdly, to apply the proposed version of algorithms to solve real life problems of engineering and reliability problems.