Dual Response Optimization via Direct Function Minimization

Abstract

Recently several authors have discussed how one can solve the three dual response problems proposed by Taguchi (target is best, larger is better, and smaller is better) without resorting to signal-to-noise ratios. The most recent articles have all relied on nonlinear programming techniques to obtain the actual solution. While these techniques certainly work, it is also possible to solve the dual response problems using the more familiar technique of direct function minimization. We demonstrate this using the Nelder-Mead simplex procedure. We also propose slightly different formulations of the problems, which seem to be more realistic. Examples for each type of dual response problem are presented.

• Multiple Responses
• Nelder-Mead Simplex Procedure
• Optimization
• Response Surface Methodology

Additional information

Notes on contributors

Karen A. F. Copeland

Dr. Copeland is a Statistician. She is a member of ASQC.

Peter R. Nelson

Dr. Nelson is a Professor of Mathematical Sciences. He is a Fellow of ASQC.