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单元制造广泛应用于柔性制造系统,计算机集成制造等自动化制造环境.针对其最关键的单元构建问题,提出了大量的单元构建方法.Joines等人将改进的遗传算法应用于处理单元构建问题.该文在其基础上考虑了每个零部件的需求量不同所带来的影响,提出了一种基于精英策略和自适应性的混合遗传算法.精英策略保证了算法的收敛性,在求解过程中不断调整交叉算子和变异算子则很好的防止了算法收敛到局部最优解.实验结果表明,该算法能高效准确的找出最优的分类结果,并能较好地在实际生产中应用.“,”Cellular manufacturing is widely used in auto-manufacturing environment such as flexible manufacturing system,computerintegrated manufacturing. While the key issue is cell formation problem(CFP),many solution methods have been developed for solving CFP such as Improved genetic algorithm proposed by Joines. Based on Joines's research,a hybrid genetic algorithm based on Elitist strategy and Adaptive genetic algorithm is proposed considering the effect of different amount of every part. Elitist strategy ensures the convergence of the algorithm and keeping on adjusting the crossover operators and the mutation operators in the procedure can prevent the algorithm from converging to a local optional solution. Experiments prove that this algorithm can get the optional classifying result effectively and accurately,and also can be used in actual manufacturing very well.