We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed software tool executing on a computational grid to solve many large instances of these problems, allowing us to obtain high-quality solutions and to verify optimality and near-optimality of the computed solutions in various ways
We study an approach for the evaluation of approximation and solution methodsfor multistage linear s...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
We investigate the quality of solutions obtained from sample-average approximations to two-stage sto...
We investigate the quality of solutions obtained from sample-average approximations to two-stage sto...
Abstract. We investigate the quality of solutions obtained from sample-average approxi-mations to tw...
Stochastic optimization problems provide a means to model uncertainty in the input data where the un...
Stochastic optimization problems provide a means to model uncertainty in the input data where the un...
Stochastic programming combines ideas from deterministic optimization with probability and statistic...
Monte Carlo sampling-based methods are frequently used in stochastic programming when exact solution...
Large scale stochastic linear programs are typically solved using a combination of mathematical prog...
Sampling and decomposition constitute two of the most successful approaches for addressing large-sca...
Large scale stochastic linear programs are typically solved using a combination of mathematical prog...
Abstract. Various stochastic programming problems can be formulated as problems of optimization of a...
Large scale stochastic linear programs are typically solved using a combination of mathematical prog...
We study an approach for the evaluation of approximation and solution methodsfor multistage linear s...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
We investigate the quality of solutions obtained from sample-average approximations to two-stage sto...
We investigate the quality of solutions obtained from sample-average approximations to two-stage sto...
Abstract. We investigate the quality of solutions obtained from sample-average approxi-mations to tw...
Stochastic optimization problems provide a means to model uncertainty in the input data where the un...
Stochastic optimization problems provide a means to model uncertainty in the input data where the un...
Stochastic programming combines ideas from deterministic optimization with probability and statistic...
Monte Carlo sampling-based methods are frequently used in stochastic programming when exact solution...
Large scale stochastic linear programs are typically solved using a combination of mathematical prog...
Sampling and decomposition constitute two of the most successful approaches for addressing large-sca...
Large scale stochastic linear programs are typically solved using a combination of mathematical prog...
Abstract. Various stochastic programming problems can be formulated as problems of optimization of a...
Large scale stochastic linear programs are typically solved using a combination of mathematical prog...
We study an approach for the evaluation of approximation and solution methodsfor multistage linear s...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...
Title: Sample approximation technique in stochastic programming Author: Eszter V¨or¨os Department: D...