A Study on Various Particle Swarm Optimization Techniques used in Current Scenario

Abstract

optimization, that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. The book by Kennedy and Bernhard describes many philosophical aspects of PSO and swarm intelligence. The Disadvantages of the particle mass optimization (PSO) algorithm are that it is easy to fall locally optimized at high dimensional space and has a low integration rate in the recirculation process. The computational complexity of DWCNPSO is accepted when used to solve high dimensional and complex problems. Particle mass optimization (PSO) is one of the bio-inspired algorithms, and finding the optimal solution in place of the solution is a simple one. It differs from other upgrade algorithms in that it requires only objective functionality and is not subject to gradient or objective particle mass optimization It does not depend on any different form, as proposed in the paper, as mentioned in the original, sociologists believe that At the school of fish or in a group A flock of migratory birds can "benefit from the experience of all other members." In other words, when a bird flies and randomly searches for food, for example, all the birds in the herd can share their findings and help the whole flock to hunt better. Optimization