Fuzzy Quantum-Behaved Particle Swarm Optimization Algorithm

Aiming at the drawback of being easily trapped into the local optima and premature convergence in quantum-behaved particle swarm optimization algorithm, fuzzy quantum-behaved particle swarm optimization algorithm was proposed. In fuzzy quantum-behaved particle swarm optimization algorithm, the center of potential of particle was influenced by more than two particles in the neighborhood and the influence was defined as fuzzy variable that is computed by Gaussian distribution. The simulation results of testing four standard benchmark functions demonstrate that fuzzy quantum-behaved particle swarm optimization algorithm has best optimization performance and robustness, the validity and feasibility of the method are verified.