Development of Chaotic Metaheuristic Algorithm for Engineering Design Problems

Abstract

Optimization is a popular domain of research and is present in every field. The field of nature inspired computing and optimization techniques have evolved to solve the difficult optimization problems in diverse fields of engineering, science and technology. According to the “No free lunch theorem,” there is no such efficient algorithm for all problems. As a result, many optimization algorithms have been developed and tried to use various improving techniques to enhance the capability of searching to see that if they can cope with these challenging optimization problems. Although many metaheuristic algorithms can accelerate the search speed, they still have major drawback of premature convergence and local optimum stagnation. Chaos theory is a novelty approach that has been widely used into various applications. Recently, numerous improvements, which rely on the chaos approach, have been proposed for metaheuristics algorithm. Spotted hyena optimizer (SHO) and Emperor penguin optimizer (EPO) are recently developed metaheuristic techniques and has been used for solving many optimization problems. The aim of this research work is to propose the chaotic version of Spotted hyena optimizer and Emperor penguin optimizer. Ten different chaotic maps will be used in this approach. The proposed approach is tested on 29 well known benchmark test functions and a comparative analysis is made with other well-known metaheuristic algorithms. The proposed chaotic algorithms are also validated on constrained engineering design problems.