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Efficient Approximation for Stochastic Optimization

Objectif

The primary goal of this research is to develop a general and constructive theory for a wide class of stochastic optimization problems in various research areas such as operations research, inventory and production management, project and machine scheduling, mathematical finance and theoretical computer science. This research project proposes to investigate efficient approximation methods for stochastic dynamic programming problems. The proposed project aims to establish when stochastic dynamic problems have FPTAS, develop generic tools to unify the creation of FPTAS, and develop efficient algorithms for realistic problems. If successful this research would lead to a better understanding of the difficulty involved in solving stochastic dynamic programming problems and to efficient approximations for stochastic optimization problems. The project is built in a modular way, exploring independently various practical topics in stochastic optimization such as stochastic models, structure of optimal policies, applied probability, dependencies of the stochastic variable, hardness results and practical performance.

Champ scientifique (EuroSciVoc)

Programme(s)

Thème(s)

Appel à propositions

FP7-PEOPLE-2009-RG
Voir d’autres projets de cet appel

Régime de financement

MC-IRG - International Re-integration Grants (IRG)

Coordinateur

THE HEBREW UNIVERSITY OF JERUSALEM
Contribution de l’UE
€ 100 000,00
Coût total
Aucune donnée