PARTICLE SWARM OPTIMIZATION

1. PARTICLE SWARM OPTIMIZATION 1-Particle Swarm Optimization:- Isused to find optimal solution to numerical and qualitative problems . 2- Particle Swarm Optimization:- used to solve unitecommitment problem. 3- Particle Swarm Optimization:- was developed by james kennedy and Russell eberhart from expriments . 4- Particle Swarm Optimization:- developed by simulation of social behavior of the brids in flocking . 5- Particles:- fly over asolution speace and land on the best solution simulating the brids behavior .

2. 6- each Particles :- should compare themselves to others and imitate the behavior of others who have achieved a particular objective successfully. 7- Eberhart and Kennedy developed a model that balances the cooperation between particles in the swarm. 8- Particle Swarm Optimization:- model to fined the best compromise between individuality and sociality or between local solution and global solution .

3. Particle Swarm Optimization Model for Continuous Variables 1- the particles are “flown” through the problem space by following the current optimum particles. Each particle keeps track of its coordinates in the problem space 2- each particle has a memory, which allows it to remember the best position on the feasible search space that it has ever visited 3-the swarmuse local optimization to get pbestand global optimization to get gbest 4- the Particle Swarm Optimization technique consists of changing the velocity of each particle toward its pbest and the gbest positions at each time step. 5- each particle tries to modify its current position and velocity according to the distance between its current position and pbest, and the distance between its current position and gbest.