A dynamic Multi-stage hybrid swarm intelligence optimization algorithm
: Each swarm’s population size
: Swarms’ number
: Regrouping period
Max_gen: Max generations, stop criterion
Step 1 Generate initial particles and set up parameters for each particle;
   Initialize the position of all particles , and their fitnesses, and
   the velocity of all particles ( ); the best local position of all particles
    ;
Step 2 Update all particles using local version PSO with Dynamic multi-group
   For
      Update each swarm using (2.2), (2.3) local version PSO, pbests and lbests updating
   If
   Regroup the swarms randomly
   End
Step 3 local search carried out in each small swarm by the artificial bee colony
   the population of food sources (solutions) is initialized by the current lbests in each
   sub-swarm
   For each component
Employed Bees’ Phase
 For each employed bee
  Replace the component of the lbest by using the component of bee
  Calculate the [ _newlbest (lbest1, lbest2 , , )]
  If ( _newlbest_ better than _lbest)
Then newlbest replaced lbest
  For employed bee produce new food source positions by using (2.4)
  Calculate the value fitness by using (2.5)
  Apply greedy selection mechanism
  End For.
End For
  Calculate the probability values for the solutions by (2.6) and (2.7) using the
  roulette wheel selection rule;
Onlooker Bees’ Phase
 For each onlooker bee
 Chooses a food source depending on
 Replace the component of the lbest by using the     component of bee
 Calculate the [newlbest](lbest1, lbest2 , )
 If (newlbest) better than (lbest)
 Then newlbest replaced lbest
 For onlooker bee produce new food source positions by using (2.4)
 Calculate the value fitness
 Apply greedy selection mechanism
 End For
End For
Scout Bees’ Phase
 If there is an employed bee becomes scout
 Then replace it with a new random source positions by using (2.8)
 Memorize the best solution achieved so far
 Compare the best solution with lbest and Memorize the better one.
Step 4 Update all particles using global version PSO
 For
 Update all particles using global version PSO, pbests and gbest updating
End
Pseudocode 1: Pseudocode of DM-PSO-ABC.