Hybrid PSO and GA for Global Maximization
K. Premalatha · 2009
This paper present the hybrid approaches of Particle Swarm Optimization (PSO) with Genetic Algorithm (GA). PSO and GA are population based heuristic search technique which can be used to solve the optimization problems modeled on the concept of Evolutionary Approach. In standard PSO, the non-oscillatory route can quickly cause a particle to stagnate and also it may prematurely converge on suboptimal solutions that are not even guaranteed to be local optimum. In this paper the modification strategies are proposed in PSO using GA. Experiment results are examined with benchmark functions and results show that the proposed hybrid models outperform the standard PSO.