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Response Surface Methodology

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Encyclopedia of Operations Research and Management Science

Introduction

Response surface methodology (RSM) is a technique to determine design factor settings to improve or optimize the performance or response of a process or product. It combines design of experiments, regression analysis and optimization methods in a general purpose strategy to optimize the expected value of a stochastic response. In their landmark paper, Box and Wilson (1951) describe the development and application of this sequential method to chemical process design, in which yields of particular compounds were maximized. Since that time the method has been applied successfully in many areas. Recent texts devoted to RSM include Myers et al. (2009) and del Castillo (2007).

Problem Setting and Background

Mathematically, RSM solves:

$$ { \max\ }f(x) \equiv {\text{E}}\left( {Y(x)} \right) $$

where Y is a random variable whose mean is an unknown function of the d-dimensional factor vector xand whose variance (arising from experimental error) is an unknown constant value,...

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Authors and Affiliations

  1. Department of Supply Chain and Information Systems, The Pennsylvania State University, 406 Business Building, University Park, PA, 16802, USA

    Russell R. Barton

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  1. Russell R. Barton
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Correspondence to Russell R. Barton .

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Editors and Affiliations

  1. Robert H. Smith School of Business, University of Maryland, College Park, MD, USA

    Saul I. Gass

  2. Robert H. Smith School of Business and Institute for Systems Research, University of Maryland, College Park, MD, USA

    Michael C. Fu

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Barton, R.R. (2013). Response Surface Methodology. In: Gass, S.I., Fu, M.C. (eds) Encyclopedia of Operations Research and Management Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1153-7_1143

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  • DOI: https://doi.org/10.1007/978-1-4419-1153-7_1143

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