Efficient, nearly orthogonal-and-balanced, mixed designs: an effective way to conduct trade-off analyses via simulation
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Authors
Vieira, H.
Sanchez, Susan M.
Kienitz, K.H.
Belderrain, M.C.N.
Subjects
simulation
design of experiments
integer programming
statistics
defense studies
design of experiments
integer programming
statistics
defense studies
Advisors
Date of Issue
2013
Date
Publisher
Language
Abstract
Designed experiments are powerful methodologies for gaining insights into the behaviour of complex simulation models. In recent
years, many new designs have been created to address the large number of factors and complex response surfaces that often arise in
simulation studies, but handling discrete-valued or qualitative factors remains problematic. We propose a framework for generating
a design, of speci!ed size, that is nearly orthogonal and nearly balanced for any mix of factor types (categorical, numerical discrete,
and numerical continuous) and mix of factor levels. These new designs allow decision makers structured methods for trade-off
analyses in situations that are not necessarily amenable to other methods for choosing alternatives, such as simulation optimization
or ranking and selection approaches. These new designs also compare well to existing approaches for constructing custom designs
for smaller experiments, and may also be of interest for exploring computer models in domains where fewer factors are involved.
Type
Article
Description
The article of record as published may be located at http://dx.doi.org/10.1057/jos.2013.14
SEED Center Paper
SEED Center Paper
Series/Report No
Department
Operations Research
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Citation
Journal of Simulation (2013) 7, pp. 264–275. doi:10.1057/jos.2013.14
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.