Robust optimization in simulation: Taguchi and Response Surface Methodology

Gabriella Dellino, Jack Kleijnen () and Carlo Meloni

International Journal of Production Economics, 2010, vol. 125, issue 1, 52-59

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. We illustrate the resulting methodology through classic Economic Order Quantity (EOQ) inventory models, which demonstrate that robust optimization may require order quantities that differ from the classic EOQ.

Keywords: Pareto; frontier; Bootstrap; Latin; hypercube; sampling (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925-5273(09)00450-2
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Robust Optimization in Simulation: Taguchi and Response Surface Methodology (2008)
Working Paper: Robust Optimization in Simulation: Taguchi and Response Surface Methodology (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:125:y:2010:i:1:p:52-59

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().