Parallel quantum evolutionary algorithm based on chaotic searching technique for multi-modal function optimization

A novel parallel quantum evolutionary algorithm based on chaotic searching technique (PCQEA) is proposed. In the algorithm, the use of a chaotic searching technique provides this methodology with superior global search ability; several antibody diversification schemes were incorporated into the algorithm in order to enhance the exploitation and exploration. It can help to obtain the multi-modal optimal solutions rapidly. The technique for improving the performance of PCQEA has been described; simulation experiments result shows that the proposed method surpasses the traditional models in regard to the convergence speed.