Gravitational Search Algorithm

Abstract

During the last decades, several metaheuristics have been developed to solve complex engineering optimization problems which most of them have been inspired by natural phenomena and swarm behaviors. Metaheuristics are the most selected techniques to find optimal solution intelligently in many areas of scheduling, space allocation, decision making, pattern recognition, document clustering, control objectives, image processing, system and filter modeling, etc. These algorithms have promised better solutions in single and multi-objective optimization. Gravitational search algorithm (GSA) is one of the recent created metaheuristic search algorithms, which is inspired by the Newtonian laws of gravity and motion. GSA was first proposed by Rashedi et al. and in the short time it became popular among the scientific community and researchers resulting in a lot of variants of the basic algorithm with improved performance. This chapter book presents a detailed review of the basic concepts of GSA and a comprehensive survey of its advanced versions. We propose a number of suggestions to the GSA community that can be undertaken to help move the area forward.