Particle swarm optimization with adaptive population size and its application
Applied Soft Computing
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
Adaptive particle swarm optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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GSA (Gravitational Search Algorithm) is inspired by the Newton's law of universal gravitation and considered as a promising evolutional algorithm, which has the advantages of easy implementation, fast convergence, and low computational cost. However, GSA has the disadvantages that its convergence speed slows down in the later search stage and it is easy to fall into local optimum solution. We proposed a novel immunity-based Gravitational Search Algorithm (IGSA) that is inspired by the biological immune system and the traditional gravitational search algorithm. The comparison experiments of GSA, IGOA and PSO (Particle Swarm Optimization) on 5 benchmark functions are carried out. The proposed algorithm shows competitive results with improved diversity and convergence speed.