Quantum-Behaved Particle Swarm Optimization with Mutation Operator
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
HIS '07 Proceedings of the 7th International Conference on Hybrid Intelligent Systems
Quantum-Behaved particle swarm optimization with adaptive mutation operator
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
A complex neighborhood based particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Information Sciences: an International Journal
Parameter tuning of a choice-function based hyperheuristic using Particle Swarm Optimization
Expert Systems with Applications: An International Journal
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This paper presents a variant of Quantum behaved Particle Swarm Optimization (QPSO) named Q-QPSO for solving global optimization problems. The Q-QPSO algorithm is based on the characteristics of QPSO, and uses interpolation based recombination operator for generating a new solution vector in the search space. The performance of Q-QPSO is compared with Basic Particle Swarm Optimization (BPSO), QPSO and two other variants of QPSO taken from literature on six standard unconstrained, scalable benchmark problems. The experimental results show that the proposed algorithm outperforms the other algorithms quite significantly.