Turbulent Particle Swarm Optimization and Genetic Algorithm for Function Maximization

The optimization problems can be solved by using population based heuristic search techniques namely Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). One of the drawbacks of standard PSO was to prematurely converge on local optimal solutions. In this work, we have used Turbulent Particle Swarm Optimization (TPSO) instead of standard PSO due to the drawback mentioned above. Here, different operations of Genetic algorithm were included to obtain a good solution. In this paper, we would like to compare the results of both algorithms. Experimental results were examined with functions which were function maximization and results show that the Turbulent PSO outperform the GA.