Pso Algorithm Is Developed By The Social Behavior Patterns Of The Organisms That Exist Essay

1658 WordsMay 20, 20167 Pages
3.3 PSO PSO algorithm is developed by the social behavior patterns of the organisms that exist and interact within large groups. As, it converges at a faster rate than the global optimization algorithms, the PSO algorithm is applied for solving various optimization problems easily. In the PSO technique, a population called as a swarm of candidate solutions are encoded as particles in the search space. Initially, PSO begins with the random initialization of the population. These particles move iteratively through the D-dimensional search space to search the optimal solutions, by updating the position of each particle. During the movement of the swarm, a vector Xi=(Xi1, Xi2,…., XiD) represents the current position of the particle ‘i’. Vi=(Vi1, Vi2,…., ViD) represents the velocity of the particle which is in the range of [−vmax, vmax]. The best previous position of a particle is denoted as personal best Pbest. The global best position obtained by the population is denoted as Gbest. The PSO searches for the optimal solution by updating the velocity and position of each particle, based on the Pbest and Gbest. The next position of the particle in the search space is calculated by using the new velocity value. This process is repeated for a fixed number of times or until a minimum error is achieved. The rate of the change in the velocity and position of the particle is given as v_id=v_id+c_1 r_1 (p_id-x_id )+c_2 r_2 (p_gd-x_id ) (3.1) x_id=x_id+v_id (3.2) Where c_1
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