State‐of‐the‐Art Optimization and Metaheuristic Algorithms

Optimization is the art of modeling for obtaining the best result under the given circumstances. Optimization aims to maximize or minimize the best effects to satisfy both the technological and managerial processes. Because of the above, this paper attempts to present a thorough and precise review of the optimization approaches applied in the fields of science and technology, incorporating modern optimization techniques based on various peer-reviewed published research papers of reputed journals. Most metaheuristics studies for multi-objective optimization (MOO) focus on evolutionary techniques and some state-of-the-art methods are part of this algorithm class. Our goal throughout this study is to explain easily accessible lines of research associated with metaheuristics but focusing on less studied areas to give fresh perspectives for those researchers who are interested in MOO. It emphasizes on non-conventional energy and distributed power generating systems along with the deregulated and regulated environment. The assessment of metaheuristic algorithms is carried out on the basis of time of computation, usage of resources, response rate, and cost of scheduling. Along with an overview, a comprehensive analysis of the metaheuristic algorithms reported in the recent past has been discussed for the assistance of new researchers concerned with this domain. A brief overview of current metaheuristic algorithms with their pros and cons is provided in this paper.