Tracking Extrema in Dynamic Environments with Quantum-behaved Particle Swarm Optimization

This paper present a global searching performance algorithm-- Quantum-behaved Particle Swarm Optimization (QPSO) algorithm applied to the complex dynamic environment. A number of experiments are performed to test the performance of the QPSO. The environments used in the experiments are generated by Dynamic Function # 1(DF1). The results of the experiments indicate that QPSO is more adaptive than Particle Swarm Optimizer (PSO) in dynamic environment.

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