Global Best Local Neighborhood in Particle Swarm Optimization in Dynamic Environment

The conventional Particle Swarm Optimization (PSO) still has weaknesses in finding optimal solutions especially in a dynamic environment. Therefore, we proposed a Global best Local Neighborhood in particle swarm optimization in order to solve the optimum solution in a dynamic environment. Based on the experimental results of 50 datasets, show that GbLN-PSO has the ability to find the quality solution in a dynamic environment