Automated response surface methodology for stochastic optimization models with unknown variance

Robin P. Nicolai*, Rommert Dekker, Nanda Piersma, Gerrit J. Van Oortmarssen

*Corresponding author for this work

Research output: Contribution to journalConference articlePopular

14 Citations (Scopus)

Abstract

Response Surface Methodology (RSM) is an optimization tool that was introduced in the early 50's by Box and Wilson (1951). In this paper we are interested in finding the best settings for an automated RSM procedure when there is very little information about the objective function. We will present a framework of the RSM procedures that is founded in recognizing local optima in the presence of noise. We emphasize both stopping rules and restart procedures. The results show that considerable improvement is possible over the proposed settings in the existing literature.

Original languageEnglish
Pages (from-to)491-499
Number of pages9
JournalProceedings - Winter Simulation Conference
Volume1
Publication statusPublished - 2004
EventProceedings of the 2004 Winter Simulation Conference - Washington, DC, United States
Duration: 5 Dec 20048 Dec 2004

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