• Nayan Ranjan Samal

Particle Swarm Optimization dynamics is one of the most important members of the swarm intelligence family. This algorithm based on population based search, which employs a number of agents, called particles, the position and velocity of which are adapted over time with an ultimate objective to search the optima in a given search landscape. The paper provides an extensive review of the diversity of the population in corporate with the Particle Swarm Optimization algorithm. It outlines the hybridization of genetic algorithm with basic algorithm, called GA-PSO, then the self adapting property introduced evolutionary hybrid EPSO. Next, the paper examines the strategy for adjustment of particle and size, the adaptive PSO. Finally it emphasises on the tuning of parameters, the tribes.

Swarm intelligence, diversity, hybridization, self adapting, and adjustment

"Analysis on Diversity of Particle Swarm Optimization ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.671-678, June-2018, Available :http://www.jetir.org/papers/JETIR1806103.pdf

"Analysis on Diversity of Particle Swarm Optimization ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp671-678, June-2018, Available at : http://www.jetir.org/papers/JETIR1806103.pdf