In the beginning we provide a brief introduction to the basic concepts of optimization and global optimization, evolutionary computation and swarm intelligence. The necessity of solving optimization problems is outlined and various types of optimization problems are discussed. A rough classfication of established optimization algorithms is provided, followed by Particle Swarm Optimization (PSO) and different types of PSO. Change in velocity component using velocity clamping techniques by bisection method and golden search method are discussed. We have discussed advantages of Using Self-Accelerated Smart Particle Swarm Optimization (SAS-PSO) technique which was introduced . Finally, the numerical values of the objective function are calculated which are optimal solution for the problem. The SAS-PSO and Standard Particle Swarm Optimization technique is compared as a result SAS-PSO does not require any additional parameter like acceleration coefficient and inertia-weight as in case of other standard PSO algorithms.
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