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 |
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