A Review on Metaheuristic Algorithms: Recent Trends, Benchmarking and Applications

Metaheuristic algorithms can be summarized as a form of stochastic optimization algorithm which does not depend on the surface gradient for optimization. These algorithms draw inspiration from various sources to improve fitness but most of these algorithms are nature inspired. They have been actively researched area due to their vast applications in engineering and artificial Intelligence application. This research area and their applications has been tremendously growing as shown through the last 2 decades research. This review paper is aimed to give a brief overview of evolutionary algorithms, their benchmarking and their recent successful applications. This paper will focus on 3 fundamental issues: state of the art algorithms, benchmarking issues and applications.