Adjustable Robust Parameter Design with Unknown Distributions
AbstractAbstract This article presents a novel combination of robust optimization developed in mathematical programming, and robust parameter design developed in statistical quality control. Robust parameter design uses metamodels estimated from experiments with both controllable and environmental inputs (factors). These experiments may be performed with either real or simulated systems; we focus on simulation experiments. For the environmental inputs, classic robust parameter design assumes known means and covariances, and sometimes even a known distribution. We, however, develop a robust optimization approach that uses only experimental data, so it does not need these classic assumptions. Moreover, we develop `adjustable' robust parameter design which adjusts the values of some or all of the controllable factors after observing the values of some or all of the environmental inputs. We also propose a new decision rule that is suitable for adjustable integer decision variables. We illustrate our novel method through several numerical examples, which demonstrate its eff ectiveness.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2013-022.
Date of creation: 2013
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Web page: http://center.uvt.nl
robust optimization; simulation optimization; robust parameter design; phi-divergence;
Find related papers by JEL classification:
- C00 - Mathematical and Quantitative Methods - - General - - - General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
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- J. MUYSKENS & C. de Neubourg, 1986. "Introduction," Discussion Papers (REL - Recherches Economiques de Louvain) 1986031, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Kleijnen, J.P.C., 2008. "Review of the book [Design and Analysis of Simulation Experiments]," Open Access publications from Tilburg University urn:nbn:nl:ui:12-4379049, Tilburg University.
- Aharon Ben-Tal & Dick den Hertog & Anja De Waegenaere & Bertrand Melenberg & Gijs Rennen, 2013.
"Robust Solutions of Optimization Problems Affected by Uncertain Probabilities,"
INFORMS, vol. 59(2), pages 341-357, April.
- Ben-Tal, A. & Hertog, D. den & De Waegenaere, A.M.B. & Melenberg, B. & Rennen, G., 2011. "Robust Solutions of Optimization Problems Affected by Uncertain Probabilities," Discussion Paper 2011-061, Tilburg University, Center for Economic Research.
- Ben-Tal, A. & Hertog, D. den & Vial, J.P., 2012. "Deriving Robust Counterparts of Nonlinear Uncertain Inequalities," Discussion Paper 2012-053, Tilburg University, Center for Economic Research.
- Kleijnen, Jack P.C., 2013. "Simulation-Optimization via Kriging and Bootstrapping: A Survey (Revision of CentER DP 2011-064)," Discussion Paper 2013-064, Tilburg University, Center for Economic Research.
- Kleijnen, Jack P.C., 2014. "Response Surface Methodology," Discussion Paper 2014-013, Tilburg University, Center for Economic Research.
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