Making a Case for Robust Optimization Models

Dawei Bai, Tamra Carpenter and John Mulvey
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Dawei Bai: Salomon Brothers Inc., 7 World Trade Center, New York, New York, 10048
Tamra Carpenter: Bellcore, 445 South Street, Morristown, New Jersey 07960
John Mulvey: Engineering and Management Systems Program, School of Engineering and Applied Science, Princeton University, Princeton, New Jersey 08544

Management Science, 1997, vol. 43, issue 7, 895-907

Abstract: Robust optimization searches for recommendations that are relatively immune to anticipated uncertainty in the problem parameters. Stochasticities are addressed via a set of discrete scenarios. This paper presents applications in which the traditional stochastic linear program fails to identify a robust solution---despite the presence of a cheap robust point. Limitations of piecewise linearization are discussed. We argue that a concave utility function should be incorporated in a model whenever the decision maker is risk averse. Examples are taken from telecommunications and financial planning.

Keywords: robust optimization; telecommunication network; financial planning; nonlinear objective; utility function; decomposition algorithm (search for similar items in EconPapers)
Date: 1997
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:43:y:1997:i:7:p:895-907

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