GA-based multi-response desirability function optimization approach

Many robust design requires the simultaneous optimization of multiple responses. Desirability function method is one of the most popular approaches for multi-response optimization, which is to use a desirability function combined with an optimization algorithm to find the most desirable settings of the controllable factors. As nondifferentiable point occurs; conventional optimization algorithms can fail to find the global optimum. This paper proposes alternative approach which is to use a desirability function combined with a genetic algorithm (GA). In particular, the problem grows even moderately in either the number of factors or the number of responses. The method is more effective. A verification example is given.