Stochastic programming

Known as: Stochastic dynamic programming, Stochastic linear program 
In the field of mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. Whereas… (More)
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Topic mentions per year

1968-2018
010020019682018

Papers overview

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Highly Cited
2016
Highly Cited
2016
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort… (More)
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Highly Cited
2014
Highly Cited
2014
This volume is an excellent guide for anyone interested in variational analysis, optimization, and PDEs. It offers a detailed… (More)
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Highly Cited
2009
Highly Cited
2009
In this paper we consider optimization problems where the objective function is given in a form of the expectation. A basic… (More)
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Highly Cited
2008
Highly Cited
2008
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org… (More)
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Highly Cited
2006
Highly Cited
2006
We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with… (More)
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Highly Cited
2006
Highly Cited
2006
Stochastic programming is the subfield of mathematical programming that considers optimization in the presence of uncertainty… (More)
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Highly Cited
2004
Highly Cited
2004
The main focus of this paper is in a discussion of complexity of stochastic programming problems. We argue that two-stage (linear… (More)
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Highly Cited
2003
Highly Cited
2003
Given a convex stochastic programming problem with a discrete initial probability distribution, the problem of optimal scenario… (More)
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Highly Cited
2003
Highly Cited
2003
We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. The uncertainty usually stems… (More)
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Highly Cited
2000
Highly Cited
2000
A major issue in any application of multistage stochastic programming is the representation of the underlying random data process… (More)
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