Research Article

Quantum Behaved Particle Swarm Optimization with Neighborhood Search for Numerical Optimization

Algorithm 2

The proposed NQPSO algorithm.
Begin
 Use opposition-based learning to generate initial population;
while FEs <= MAX_FEs do
  for each particle i do
   Update the position according to (3);
   Calculate the fitness value of the new particle;
   FEs++;
   if rand( )   then
    Generate a new particle according to (5);
    Generate a new particle according to (6);
    Calculate the fitness values of the two new particles;
    Fes = Fes + 2;
    Select the fittest one among particle i and two new particles as the new particle i;
   end if
   Update the pbest,   gbest and p in the population;
  end for
end while
End