Abstract: Desirability function method uses a desirability function combined with an optimization algorithm to find the most desirable settings of the controllable factors.As nondifferentiable point occurs,the problem grows even moderately in either the number of factors or the number of responses,conventional optimization algorithms can fail to find the global optimum.This paper proposes alternative approach which uses a desirability function combined with a Genetic Algorithm（GA）.The example shows the proposed GA approach effectively solves multiple－response problems．

摘要： 满意度函数法应用优化算法对总体满意度函数最大化求解,获得最佳因子组合。然而,满意度函数有时不可微,随因子、响应个数的增加,问题变复杂时,传统的优化算法可能获得局部最优解。提出一种基于遗传算法的满意度多响应优化方法。实例验证了该方法的有效性。