Particle Swarm Optimization Algorithm with Multiple Phases for Solving Continuous Optimization Problems

Algorithm 2

Basic procedure of PSO algorithm with multiple phase strategy.

(1)	Initialize each particle’s velocity and position with random numbers;
(2)	while not reaches the maximum iteration or not found the satisfied solution do
(3)	Calculate each solution’s function value;
(4)	Compare function value between the current position and the best position in history (personal best, termed as ). For each particle, if current position has a better function value than , then update as current position;
(5)	Selection a particle which has the best fitness value among current particle’s neighborhood, this particle is termed as the neighborhood best;
(6)	for each particle do
(7)	Update the particle’s velocity according equation (1);
(8)	Update the particle’s position according equation (2);
(9)	Change the search phase: update the structure and/or parameter settings;