The quantum genetic algorithm is a kind of probability evolution algorithm but when it solves multimodal optimization problems

the update strategy of rotation gate will easy lead to local optimal solution and also cant find all best solutions in some optimization problem.Therefore in this paper a multi-population synergy quantum genetic algorithm (MPSGQA) proposed to solve these problems and find all the best solutions.The main idea is dividing sub-populations by using clustering analysis and the update them. If some of the sub-populations have large similarity

the quantum mutation strategy is adopted to maintain the diversity of population. Experiment and comparison with multimodal optimization function F to F

the result shows that MPSGQA can jump out of local optimal solution better than quantum genetic algorithm and find all global optimum solutions efficiently.