Research Article

On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization

Algorithm 3

Inertia weight PSO algorithm.
Begin Algorithm
     Input: function to optimize,
       swarm size,
       problem dimension,
       search space range,
       velocity range,
     Output: : the best value found
     Initialize:  for all particles in problem space
             and
             ,
     Evaluate in variables and get ,
      best best of
      Repeat
          Calculate
          Update for all particles using (1)
          Update for all particles using (2)
          Evaluate in variables and get ,
          If is better than then
          If the best of is better than best then best best of
     Until Stopping criteria (e.g., maximum iteration or error tolerance is met)
      best
     Return
End Algorithm