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A Unified Approach for Dual Response Surface Optimization

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Optimal Experimental Design Methods Advanced Optimization Algorithms Research Advanced Multi-Objective Optimization Algorithms

Abstract

This chapter contains sections titled: Introduction Review of Existing Techniques for Dual Response Surface Optimization Example 1 Example 2 Conclusions References

Citations in this library

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References

1980Simultaneous Optimization of Several Response Variables 1990Combining Taguchi and Response Surface Philosophies: A Dual Response Approach 1995Dual Response Surface Optimization 1981Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions 1993STRATEGIES FOR ROBUST MULTIRESPONSE QUALITY ENGINEERING 1993A Nonlinear Programming Solution to the Dual Response Problem 1999Response Surface Methodology—Current Status and Future Directions 1973Response Surface Techniques for Dual Response Systems

Cited by

2018A desirability function method for optimizing mean and variability of multiple responses using a posterior preference articulation approach 2007Fortification of Six Sigma: expanding the DMAIC toolset 2012Ensemble of Surrogates for Dual Response Surface Modeling in Robust Parameter Design 2008Another view of dual response surface modeling and optimization in robust parameter design 2008Log-Normal Versus Gamma Models for Analyzing Data from Quality-Improvement Experiments 2012An Overview of Optimization Formulations for Multiresponse Surface Problems 2005Mean square error criteria to multiresponse process optimization by a new genetic algorithm 2011Interactive weighting of bias and variance in dual response surface optimization

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