A swarm is a large number of homogenous simple agents interacting locally among themselves and their environment with no central control to allow a global interesting behavior to emerge. Swarm-based algorithms have recently emerged as a family of nature-inspired, population-based algorithms that are capable of producing low cost, fast, and robust solutions to several complex problems. Swarm Intelligence (SI) is a new branch of Artificial Intelligence (AI) used to model the collective behavior of social swarms in nature such as ant colonies, honey bees and bird flocks. In the present paper a swarm intelligence based computational technique named particle swarm optimization (PSO) algorithm has been tried in solving a set of problems of engineering optimization which are given in appendix of this paper. PSO was originally used to solve non-linear continuous optimization problems but more recently it has been used in many practical real life application problems mainly in engineering.
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