Algorithm 1. PSO-SA Algorithm

itr = 1  Initialize swarm size, T,ᾳ  Initialize particle Position and Velocity  Stop Condition = maxiterations or predefine error  while Not stop Condition do     for each particle I = 1 to swarm size, do        Evaluate f(particle(i))      if the f(particle(i)) is better than the f(Pbest) then         Update current Pbest.     end     if f(Pbest) is better than f(Gbest) then        Gbest = Pbest     end   end   if f(Gbest) > predefine error then     Generate neighborhoods(Gbest, ᾳ)     For j = 1 to neighborhoods size do        Evaluate f(Neighborhood(j))        if the f(Neighborhood(j)) is better than the f(Gbest) then       Gbest = Neighborhood(j)        Elseaccept the Neighborhood with a probability p defined by       ∆E = f(Neighborhood(i).Pbest) − f(Gbest)       P = e−∆E/T        end        update T    end   update ᾳ   itr = itr + 1 endupdate ᾳ itr = itr + 1 end