A quantum-behaved particle swarm optimization algorithm with extended elitist breeding

A quantum-behaved particle swarm optimization with extended elitist breeding (EEB-QPSO) is proposed in this paper. In the proposed EEB-QPSO algorithm, the superior solutions found in the whole evolution process so far are regarded as the elitists and stored in an extra memory pool, and followed by elitist breeding strategy with some operators performed on extended elitists to improve the global search ability of the algorithm. Experiments testing on the unimodal and multimodal benchmark functions showed that the proposed EEB-QPSO is better than the original QPSO and EB-QPSO in terms of global search capability and convergence speed.