Robust Optimization in Simulation: Taguchi and Response Surface Methodology

G. Dellino, J.P.C. Kleijnen, C. Meloni

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Abstract

Optimization of simulated systems is tackled by many methods, but most methods assume known environments. This article, however, develops a 'robust' methodology for uncertain environments. This methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by Response Surface Methodology (RSM). George Box originated RSM, and Douglas Montgomery recently extended RSM to robust optimization of real (non-simulated) systems. We combine Taguchi's view with RSM for simulated systems, and apply the resulting methodology to classic Economic Order Quantity (EOQ) inventory models. Our results demonstrate that in general robust optimization requires order quantities that differ from the classic EOQ.
Original languageEnglish
Place of PublicationTilburg
PublisherOperations research
Number of pages41
Volume2008-69
Publication statusPublished - 2008

Publication series

NameCentER Discussion Paper
Volume2008-69

Keywords

  • Pareto frontier
  • bootstrap
  • Latin hypercube sampling

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