Abstract: In high-dimensional complex function optimization,quantum evolutionary algorithm is easy to fall into local optimal solution and convergence speed slower in the later stage of evolution,in order to improve its search performance further,this paper proposes a segmented quantum evolutionary algorithm which introduces simplex search operator,the search process is divided into three stages,first,use quantum evolutionary algorithm to search a certain times,then divided the population into a number of sub-populations,each individual of sub-populations as the initial vertex of the simplex method and parallel search using the simplex method,merge the sub-populations after search,use quantum evolutionary algorithm continue to the last searching．The simulation results of several typical high-dimensional function show that this algorithm has faster convergence speed and higher accuracy.

Key words: Quantum evolution,Simplex method,Optimization