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.