Comparison of Swarm Intelligence Techniques

Thakare S. A.

Abstract


Swarm intelligence is a computational intelligence technique to solve complex real-world problems. It involves the study of collective behaviour of behavior of decentralized, self-organized systems, natural artificial. Swarm Intelligence (SI) is an innovative distributed intelligent paradigm for solving optimization problems that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates.  In this paper, we have made extensive analysis of the most successful methods of optimization techniques inspired by Swarm Intelligence (SI): Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). An analysis of these algorithms is carried out with fitness sharing, aiming to investigate whether this improves performance which can be implemented in the evolutionary algorithms.


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