Galaxy gravity optimization(GGO) an algorithm for optimization, inspired by comets life cycle

The aim of this paper is to propose an optimization algorithm which is inspired by the comet's life. Like other evolutionary algorithms, this proposed algorithm commences with an initial population. The individuals of the population are comets which are composed of two parts: a nucleus and small celestial bodies. These comets after exit of Kuiper belt due to the gravitational disorder which has been triggered by solar system planets, and entering to the solar system, start the main competition for more survival in the solar system. Along this competition the weakened comets collapse and convert to rubbles along the solar orbit which comets where orbiting and other comets depending on their gravitational power relatively absorb these rubbles (small celestial bodies). The comet which has been able to lose least of its mass and gain the most, along its orbits and based on gravitational mutation (having better orbits); has been able to spend more time in solar system so it converges with a higher fitness function in a global maximum. The results of the proposed algorithm which have been experimented on some benchmark functions, represent that this algorithm is capable of dealing with a variety of optimization problems.