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。
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.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第31期48-49,95,共3页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.70572044)
关键词
满意度函数
回归模型
响应曲面
遗传算法
desirability functions
regression modeling
response surface
Genetic Algorithm(GA)