Results 261 to 270 of about 21,299,052 (294)

Formulating Two-Stage Stochastic Programs for Interior Point Methods

Operations Research, 1991
This paper describes an approach for modeling two-stage stochastic programs that yields a form suitable for interior point algorithms. A staircase constraint structure is created by replacing first stage variables with sparse “split variables” in conjunction with side-constraints. Dense columns are thereby eliminated.
Irvin J. Lustig, John M. Mulvey, Tamra J. Carpenter   +2 more
openaire   +1 more source

A two-stage stochastic programming model for electric energy producers

Computers & Operations Research, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Patrizia Beraldi, Domenico Conforti, Antonio Violi   +2 more
openaire   +3 more sources

Two-Stage Stochastic Programming Problems

1995
In this chapter we consider stochastic programming problems where decisions are made in two stages and the observation of a (vector valued) random variable takes place in between. Such problems are called two-stage stochastic programming problems or stochastic programming with recourse.
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Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse

Mathematics of Operations Research, 1991
We present a cutting plane algorithm for two-stage stochastic linear programs with recourse. Motivated by Benders' decomposition, our method uses randomly generated observations of random variables to construct statistical estimates of supports of the objective function.
Julia L. Higle, Suvrajeet Sen
openaire   +3 more sources

A regularized stochastic decomposition algorithm for two-stage stochastic linear programs

Computational Optimization and Applications, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Stochastic decomposition for risk-averse two-stage stochastic linear programs

Journal of Global Optimization
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Prasad Parab, Lewis Ntaimo, Bernardo K. Pagnoncelli   +2 more
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Risk Aversion in Two-Stage Stochastic Integer Programming

2010
Some recent developments in the area of risk aversion in stochastic integer programming are surveyed. After a discussion of modeling guidelines and resulting mean–risk stochastic integer programs emphasis is placed on structural properties of these optimization problems and on algorithms for their solution. Bibliographical notes conclude the Chapter.
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Multi-Period Active Distribution Network Planning Using Multi-Stage Stochastic Programming and Nested Decomposition by SDDIP

IEEE Transactions on Power Systems, 2021
Pengwei Du, Ming Qu, Can Huang
exaly  

Risk objectives in two-stage stochastic programming models

Kybernetika, 2008
Summary: In applications of stochastic programming, optimization of the expected outcome need not be an acceptable goal. This has been the reason for recent proposals aiming at construction and optimization of more complicated nonlinear risk objectives. We will survey various approaches to risk quantification and optimization mainly in the framework of
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Stability in two-stage multiobjective stochastic programming

Nonlinear Analysis: Theory, Methods & Applications, 2001
openaire   +1 more source