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For a decade swarm Intelligence deals with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behavior of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. The aim of this review paper is to analyze and compare various swarm intelligence evolutionary techniques of load balancing and conclude the best optimum technique among them. A brief introduction of load balancing and its various evolutionary techniques are presented and summarized.
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