Table 2.

Pseudocode of GM-CPSO.

-- Determine the parameter values and ranges -- Assign the first positions -- Calculate the error or profit -- Define ${\mathit{X}}_{pbest\left(i\right)}$(0) $={\mathit{X}}_i$(0) and ${\mathit{X}}_{gbest}$(0) $=$ best(${\mathit{X}}_{pbest\left(i\right)}$(0)) -- Update the inertia weight vector according to the maximum iteration number $\to$ (3) While (iteration < maximum iteration number)  -- Computation of new velocity and position vectors $\to$ (1) and (2)  -- Calculate the error or profit  If (minimum error or maximum profit is reached)  -- Save the best particle vector and its fitness  -- Break  End  -- Attain the ${\mathit{X}}_{pbest}$ vector for every particle and ${\mathit{X}}_{gbest}$ for the entire swarm  -- iteration++ End