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Version Date Utilisateur ID du Champ Champ Difference
4 10 mai 2012 09:53 abdel.lisser 183 Objectives
 Our objectives in this projet are fourfold: Our objectives in this projet are fourfold:
-1.Study new algorithms based on stochastic gradient methods for solving stochastic bilevel combinatorial optimization problems with equilibrium constraints. This first part should allow to study later on stochastic game theory problems. +1.Study new algorithms based on stochastic gradient methods for solving stochastic bilevel combinatorial optimization problems with equilibrium constraints.
 2. Application of such algorithms for solving stochastic bilevel combinatorial optimization problems. Both theoritical and algorithmic aspects will be considered. 2. Application of such algorithms for solving stochastic bilevel combinatorial optimization problems. Both theoritical and algorithmic aspects will be considered.
3 10 mai 2012 09:50 abdel.lisser 180 Abstract
-Study of stochastic bilevel programming with applications to ernergy management and network design problems. +Study of stochastic bilevel programming with applications to energy management and network design problems.
2 10 mai 2012 09:49 abdel.lisser 180 Abstract
-University of Duisburg-Essen, NTNU, University of Hong Kong, Canada, Brazil +Study of stochastic bilevel programming with applications to ernergy management and network design problems.
      182 Work program
-The candidate will work on the approaches developed within GraphComb team, namely GLCP methods, stochastic gradient methods with continuous distributions as well as the state of the art in stochastic programming. He/She will also work on game theory methods in order to handle the equilibrium constraints. This will make a bridge between stochastic combinatorial bilevel programming and stochastic game theory. The following stage will concern studies and proposal of new approaches for solving stochastic game theory problems. +The candidate will work on the approaches developed within GraphComb team, namely GLCP methods, stochastic gradient methods with continuous distributions as well as the state of the art in stochastic programming. Special interest will be given to chance constraint problems together with bilevel optimization.
      183 Objectives
 1.Study new algorithms based on stochastic gradient methods for solving stochastic bilevel combinatorial optimization problems with equilibrium constraints. This first part should allow to study later on stochastic game theory problems. 1.Study new algorithms based on stochastic gradient methods for solving stochastic bilevel combinatorial optimization problems with equilibrium constraints. This first part should allow to study later on stochastic game theory problems.
-2. Application of such algorithms for solving stochastic bilevel combinatorial optimization problems as well as stochastic game theory problems. Both theoritical and algorithmic aspects will be considered. +2. Application of such algorithms for solving stochastic bilevel combinatorial optimization problems. Both theoritical and algorithmic aspects will be considered.
 3. Derive tight bounds and efficient algorithms for such problems. 3. Derive tight bounds and efficient algorithms for such problems.
 4. Applications will be considered in the area of network design problems and energy planning problems. 4. Applications will be considered in the area of network design problems and energy planning problems.
1 10 mai 2012 09:41 abdel.lisser 190 Year
-2011 +2012

Ecole Doctorale Informatique Paris-Sud

Directrice
Nicole Bidoit
Assistante
Stéphanie Druetta
Conseiller aux thèses
Dominique Gouyou-Beauchamps
ED 427 - Université Paris-Sud
UFR Sciences Orsay
Bat 650 - aile nord - 417
Tel : 01 69 15 63 19
Fax : 01 69 15 63 87
courriel: ed-info à lri.fr