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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… Expand
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Papers overview

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Highly Cited
2013
Highly Cited
2013
In this paper, we introduce a new stochastic approximation (SA) type algorithm, namely the randomized stochastic gradient (RSG… Expand
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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… Expand
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Highly Cited
2009
Highly Cited
2009
“SPbook”2009/5/4page iiiiiiiiiiDarinka DentchevaDepartment of Mathematical SciencesStevens Institute of TechnologyHoboken, NJ… Expand
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Highly Cited
2003
Highly Cited
2003
We consider convex stochastic programs with an (approximate) initial probability distribution P having finite support supp P, i.e… Expand
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Highly Cited
2000
Highly Cited
2000
Given a convex stochastic programming problem with a discrete initial probability distribution, the problem of optimal scenario… Expand
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Highly Cited
2000
Highly Cited
2000
Abstract Markov decision processes (MDPs) have proven to be popular models for decision-theoretic planning, but standard dynamic… Expand
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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… Expand
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Highly Cited
1998
Highly Cited
1998
 
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Highly Cited
1995
Highly Cited
1995
When formulating a stochastic programming problem, we usually start from a deterministic problem that we call underlying… Expand
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Highly Cited
1989
Highly Cited
1989
 
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