STOCHASTICOPT

Efficient Approximation for Stochastic Optimization

Coordinatore	THE HEBREW UNIVERSITY OF JERUSALEM.    more  Organization address address: GIVAT RAM CAMPUS city: JERUSALEM postcode: 91904 contact info Titolo: Ms. Nome: Jane Cognome: Turner Email: send email Telefono: -6585706 Fax: -6512235
Nazionalità Coordinatore	Israel [IL]
Totale costo	100˙000 €
EC contributo	100˙000 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2009-RG
Funding Scheme	MC-IRG
Anno di inizio	2010
Periodo (anno-mese-giorno)	2010-04-01   -   2014-03-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	THE HEBREW UNIVERSITY OF JERUSALEM.  Organization address address: GIVAT RAM CAMPUS city: JERUSALEM postcode: 91904 contact info Titolo: Ms. Nome: Jane Cognome: Turner Email: send email Telefono: -6585706 Fax: -6512235	IL (JERUSALEM)	coordinator	100˙000.00

Mappa

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 Obiettivo del progetto (Objective)

'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.'

Introduzione (Teaser)

Most real-world 'problems' are stochastic or random in nature. Scientists developed novel optimisation algorithms for solving these complex problems and used them to address issues of inventory control and finance.