Comparative study of state-of-the-art metaheuristics for solving constrained mechanical design optimization problems: experimental analyses and performance evaluations

Many challenges are involved in solving mechanical design optimization problems related to the real-world, such as conflicting objectives, assorted design variables, discrete search space, intuitive flaws, and many locally optimal solutions. A comparison of algorithms on a given set of problems can provide us with insights into their performance, finding the best one to use, and potential improvements needed in their mechanisms to ensure maximum performance. This motivated our attempts to comprehensively compare eight recent meta-heuristics on 15 mechanical engineering design problems. Algorithms considered are water wave optimizer (WWO), butterfly optimization algorithm (BOA), Henry gas solubility optimizer (HGSO), Harris Hawks optimizer (HHO), ant lion optimizer (ALO), whale optimization algorithm (WOA), sine-cosine algorithm (SCA) and dragonfly algorithm (DA). Comparative performance analysis is based on the solution trait obtained from statistical tests and convergence plots. The results demonstrate the wide range of adaptability of considered algorithms for future applications.