BOSCA—A Hybrid Butterfly Optimization Algorithm Modified with Sine Cosine Algorithm

Nature-inspired metaheuristic algorithms along with their improved and hybrid versions have been gaining intrinsic popularity in solving nonlinear constrained complex real-world problems. On this presentation, a new hybrid butterfly optimization algorithm (BOA), viz. BOSCA combined with sine cosine algorithm (SCA) is suggested to develop a balanced yet powerful optimization technique through enhancing and stabalizing the global exploration and local exploitation ability. In this, metaheuristic hybridization is done in such a way to get both the exploration and exploitation phases for each of the butterfly with sufficient chance to improvise each solution. To prove the efficiency and robustness of the developed BOSCA, it has been applied to solve twenty-five classical benchmark functions. A comparative study has been done by taking some of the popular algorithms in available in literature and this developed algorithm is found to be superior to the compared algorithms. Again to validate its efficiency in real-world problems, it has been applied to two real-world problems; One is gas transmission compressor design problem and another is optimal capacity of gas production facilities. Results of these real-world problems have been compared to that of some other algorithms and the proposed method found to be superior in real-world optimization problems also.