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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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publications
Decomposition-Coordination method for the management of a chain of dams
Authors: J-C. Alais, P. Carpentier, V.Leclère
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Priority option : the value of being a leader
Authors: M. Grasselli, V.Leclère, M. Ludkovski
Published in International Journal of Theoretical and Applied Finance, 2013
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Optimization Methods for the Smart Grid
Authors: P. Carpentier, J-Ph. Chancelier, M. De Lara, V.Leclère
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On the convergence of decomposition methods for multistage stochastic convex programs
Authors: P. Girardeau, V.Leclère, A. Philpott
Published in Mathematics of Operations Research, 2015
Asymptotic convergence of SDDP algorithms in the non-linear convex case.
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Building up time-consistency for risk measures and dynamic optimization
Authors: M. De Lara, V. Leclère
Published in European Journal of Operational Research, 2016
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Probabilistic Approach to One-Class Support Vector Machine
Authors: V. Leclère, E. Grave, L. El Ghaoui
A new derivation of the one-class SVMs paradigms.
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Efficient smoothed concomitant lasso estimation for high dimensional regression
Authors: E. Ndiaye, O. Fercoq, A. Gramfort, V. Leclère, J. Salmon
Published in Journal of Physics: Conference Series, 2017
Safe screen rules for square-root lasso
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On risk averse competitive equilibrium
Authors: H. Gérard, V.Leclère, A. Philpott
Published in Operations Research Letters, 2018
Showcasing multiple equilibria due to risk-aversion
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Stochastic Multi-item Lot-sizing Problem with Bounded Number of Setups
Authors: E. De Saint Germain, F. Meunier, V. Leclère
A model balancing costs, stocks and flexibility in the supply chain.
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Stochastic decomposition applied to large-scale hydro valleys management
Authors: P. Carpentier, J-Ph. Chancelier, F. Pacaud, V.Leclère
Published in European Journal of Operational Research, 2018
Application of DADP and other decomposition methods to large-scale hydro problem
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Epiconvergence of relaxed stochastic optimization problems
Authors: V. Leclère
Published in Operations Research Letters, 2019
Epiconvergence of approximated problems appearing in DADP
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Exact converging bounds for Stochastic Dual Dynamic Programming via Fenchel duality
Authors: V. Leclère, P. Carpentier, J-Ph. Chancelier, F. Pacaud
Published in SIAM journal on Optimization, 2020
Theory and convergence of dual SDDP
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Integer Programming on the Junction Tree Polytope for Influence Diagrams
Authors: A. Parmentier, V. Cohen, V. Leclère, J. Salmon, G. Obozinski
Published in INFORMS Journal on Optimization, 2020
Mathematical Programming methods for stochastic problems with structured information
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Generalized adaptive partition-based method for two-stage stochastic linear programs: Geometric oracle and analysis
Authors: M. Forcier, V. Leclère
Published in Operation Research Letters, 2022
Generalized adaptive partition-based method for two-stage stochastic linear programs: Geometric oracle and analysis
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Robust Optimization Applied to Uncertain Limit Analysis
Authors: J. Bleyer, V. Leclère
Published in Direct Methods for Limit State of Materials and Structures,, 2023
This work proposes a novel theoretical framework of robust limit analysis i.e. the computation of limit loads of structures in presence of uncertainties using limit analysis and robust optimization theories.
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Dual SDDP for risk-averse multistage stochastic programs
Authors: B. Da Costa, V. Leclère
Published in Operation Research Letters, 2023
We apply a dual SDDP approach to risk averse problem.
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Joint Production and Energy Supply Planning of an Industrial Microgrid
Authors: Z. Fornier, D. Grosso, V. Leclère
Published in , 2023
Joint Production and Energy Supply Planning of an Industrial Microgrid
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Duality of upper bounds in stochastic dynamic programming
Authors: B.F.P da Costa, V. Leclère
Duality of upper bounds in stochastic dynamic programming
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Exact quantization of multistage stochastic linear problems
Authors: M. Forcier, S. Gaubert, V. Leclère
Published in SIAM journal on Optimization, 2023
We show that MLSP with arbitrary cost are equivalent to MLSP with discrete cost and give a geometrical insight to the discretization procedure. Best student paper at ECSO-CMS 2022.
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Convergence of Trajectory Following Dynamic Programming algorithms for multistage stochastic problems without finite support assumptions
Authors: M. Forcier, V. Leclère
Published in Journal of Convex Analysis, 2023
Convergence of Trajectory Following Dynamic Programming algorithms for multistage stochastic problems without finite support assumptions
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Joint production and energy supply planning of an industrial microgrid
Authors: Z. Fornier, D. Grosso, P. Pinson
Published in Energy Systems, 2024
Joint production and energy supply planning of an industrial microgrid
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Fairness by design in shared-energy allocation problems
Authors: Z. Fornier, V. Leclère, P. Pinson
Fairness by design in shared-energy allocation problems
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Policy with guaranteed risk-adjusted performance for multistage stochastic linear problems
Authors: B. Da Costa, V. Leclère
Policy with guaranteed risk-adjusted performance for multistage stochastic linear problems
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Strategic behavior of risk-averse agents under stochastic market clearing
Authors: A. Philpott, V. Leclère
Strategic behavior of risk-averse agents under stochastic market clearing
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talks
SAFE elimination of variables
Published:
SAFE elimination of variables. slides
Decomposition Methods in Stochastic Optimization
Published:
Tutorial on decomposition methods for optimization under uncertainty. slides
Decompositions Methods in Stochastic Optimization (extended version)
Published:
Tutorial on decompositions methods for optimization under uncertainty. slides
Stochastic Programming or Dynamic Programming ?
Published:
Tutorial on Stochastic Programming and Dynamic Programming methods for optimization under uncertainty. slides
Computing risk averse equilibrium in incomplete market.
Published:
Showcasing multiple equilibria in a competitive market with risk averse players. slides paper
Exact and converging bounds for SDDP.
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Presentation of the dual SDDP algorithm yielding exact upper bounds. slides paper
A new look at SDDP.
Published:
Presentation of the dual SDDP algorithm yielding exact upper bounds. slides paper
A dual SDDP algorithm.
Published:
Presentation of the dual SDDP algorithm yielding exact upper bounds. slides paper
Exact quantization methods for MSLP.
Published:
In this talk we explain how to obtain local and uniform exact discretization of linear stochastic problems. slides
Convergence theory of Trajectory Following Dynamic Programming algorithms.
Published:
In this talk we give a framework for Trajectory Following Dynamic Programming algorithms and provide convergence result that does not require a finitely supported noise assumption slides preprint
teaching
Stochastic Optimization
Graduate course, IPP, M2, 2022
This is a master level course about stochastic optimization that take place at ENSTA-Paris, room 1226. See here for access information. You will need an identification document to get in the school.
Convex optimization
Undergraduate course, Ecole des Ponts, 2A, 2022
This is a 4th year course about continuous (mainly convex) optimization.
Operation Research and transport
Undergraduate course, Ecole des Ponts, 1A, 2022
This is a 3rd year course about the use of Operation Research in Transport problem. The subject being incredibly vast we actually focus on traffic assignement problem : knowing where people want to go, how is everybody going to choose its path, the traffic equilibrate and finally how much traffic jam are we going to observe.
Optimization Under Uncertainty
Graduate course, MPRO, M2, 2023
This is a master level course about optimization under uncertainty, that take place at CNAM, (various room). See here for access information (“Matières” then “MPRO”).
tutorials
Introduction to Stochastic Programming.
Published:
We present the basis of modeling under uncertainty, value and price of information, and sample average approximation. slides
Introduction to Decomposition Methods in Stochastic Optimization.
Published:
In this long tutorial we cover various decompositions techniques for stochastic optimization:
Introduction to (static) Robust Optimziation.
Published:
In this tutorial we cover basic elements on Robust Optimization:
Stochastic Programming or Dynamic Programming.
Published:
We present the basis of stochastic and dynamic programming and ends with example comparing both approaches and limits. slides
Trajectory Following Dynamic Programming.
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We present the Stochastic Dual Dynamic Programming algorithm and some of his brethren. slides