Abstract：To solve the problem of slow convergence speed,slow accuracy and easily falling into local optimum in the updating process of volleyball premier league algorithm(VPL),a kind of novel volleyball premier league algorithm(NVPL)was proposed.Firstly,the super star player was introduced into the volleyball league to enhance the searching ability and efficiency of the algorithm.Secondly,by improving the substitute operator,the algorithm can choose whether to call the substitute or not adaptively.Finally,the new team vector is generated dynamically by means of random crossover for the global optimization problem,i.e.,the worst team learning from the best team and the random selected other team learning from the best team with different strategies.The random crosser learning strategy is applied to balance the global search and local search performance of the algorithm.Simulation test experiments on eleven classical functions show the NVPL has better performance.
胡亚东,马良,刘勇. 新型排球超级联赛算法[J]. 小型微型计算机系统, 2020, 41(10): 2109-2115.
HU Ya-dong,MA Liang,LIU Yong. Novel Volleyball Premier League Algorithm. Journal of Chinese Computer Systems, 2020, 41(10): 2109-2115.
2020, Vol. 41 
