Correlated Simulation Experiments in First-Order Response S

The collection of mathematical models, experimental strategies, and statistical inference, referred to as response surface methodology (RSM), has been employed in the empirical exploration of a wide variety of systems, especially for industrial situations in which many variables affect the system re...

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Bibliographic Details
Published inOperations research Vol. 35; no. 5; p. 744
Main Authors Hussey, James R, Myers, Raymond H, Houck, Ernest C
Format Journal Article
LanguageEnglish
Published Linthicum Institute for Operations Research and the Management Sciences 01.09.1987
Subjects
Correlation analysis
Mathematical models
Methods
Operations research
Simulation
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Summary:The collection of mathematical models, experimental strategies, and statistical inference, referred to as response surface methodology (RSM), has been employed in the empirical exploration of a wide variety of systems, especially for industrial situations in which many variables affect the system response of interest. Experimental strategies for implementing RSM procedures in a simulation setting are examined. Analysis of correlation induction strategies is based on variance criteria often used in response surface design, including: 1. generalized variance, 2. prediction variance, 3. integrated variance, and 4. variance of slopes. The findings demonstrate that the simultaneous use of common and antithetic stream sets is the preferred correlation induction strategy but that no one assignment method is uniformly superior for all 4 criteria.
ISSN:0030-364X
1526-5463