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» Scenarios for Multistage Stochastic Programs
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FOCS
2005
IEEE
14 years 1 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
DAGSTUHL
2007
13 years 9 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
CDC
2008
IEEE
110views Control Systems» more  CDC 2008»
14 years 2 months ago
Multistage investments with recourse: A single-asset case with transaction costs
— We consider a financial decision problem involving dynamic investment decisions on a single risky instrument over multiple and discrete time periods. Investment returns are as...
Ufuk Topcu, Giuseppe Carlo Calafiore, Laurent El G...
CCE
2004
13 years 7 months ago
Optimization under uncertainty: state-of-the-art and opportunities
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncer...
Nikolaos V. Sahinidis
CCE
2010
13 years 5 months ago
A simple heuristic for reducing the number of scenarios in two-stage stochastic programming
In this work we address the problem of solving multiscenario optimization models that are deterministic equivalents of two-stage stochastic programs. We present a heuristic approx...
Ramkumar Karuppiah, Mariano Martín, Ignacio...