425 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR43 papers
- EDF Energy (United Kingdom)GB24 papers
- CERMICSFR17 papers
- Université Paris-SaclayFR17 papers
- Institut de Mathématiques de ToulouseFR16 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR14 papers
- Institut national de recherche en sciences et technologies du numériqueFR14 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR14 papers
- Université Toulouse III - Paul SabatierFR13 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR12 papers
- École PolytechniqueFR12 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR12 papers
28 papers · 1 filter
BORWin: Exact algorithm based on a Bi-Objective Relaxation for Window-constrained problems
Christian Artigues, Pascale Bendotti, Alexandre Heintzmann +2
A mixed integer maximization problem involving several additional constraints defined with both a lower and an upper bound is considered. It is assumed that one of such constraints…
Online Markov Decision Processes with Terminal Law Constraints
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard +1
Traditional reinforcement learning usually assumes either episodic interactions with resets or continuous operation to minimize average or cumulative loss. While episodic settings…
Temporal and Spatial Decomposition for Prospective Studies in Energy Systems under Uncertainty
Camila Martinez Parra, Michel de Lara, Jean-Philippe Chancelier +2
The increasing penetration of renewable energy requires greater use of storage resources to manage system intermittency. As a result, there is growing interest in evaluating the op…
An entropy penalized approach for stochastic optimization with marginal law constraints. Complete version
Thibaut Bourdais, Nadia Oudjane, Francesco Russo
This paper focuses on stochastic optimal control problems with constraints in law, which are rewritten as optimization (minimization) of probability measures problem on the canonic…
State-space reduction techniques exploiting specific constraints for quantum search Application to a specific job scheduling problem
Rodolphe Griset, Ioannis Lavdas, Jiri Guth Jarkovsky
Quantum search has emerged as one of the most promising fields in quantum computing. State-of-the-art quantum search algorithms enable the search for specific elements in a distrib…
Growth model with externalities for energetic transition via MFG with common external variable
Pierre Lavigne, Quentin Petit, Xavier Warin
This article introduces a novel mean-field game model for multi-sector economic growth in which a dynamically evolving externality, influenced by the collective actions of agents,…
Optimizing Flexibility in Power Systems by Maximizing the Region of Manageable Uncertainties
Aron Zingler, Stephane Fliscounakis, Patrick Panciatici +1
Motivated by the increasing need to hedge against load and generation uncertainty in the operation of power grids, we propose flexibility maximization during operation. We consider…
A Two-Timescale Decision-Hazard-Decision Formulation for Storage Usage Values Calculation
Camila Martinez Parra, Michel de Lara, Jean-Philippe Chancelier +3
The penetration of renewable energies requires additional storages to deal with intermittency. Accordingly, there is growing interest in evaluating the opportunity cost (usage valu…
Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard +1
Many machine learning tasks can be solved by minimizing a convex function of an occupancy measure over the policies that generate them. These include reinforcement learning, imitat…
An entropy penalized approach for stochastic control problems. Complete version
Thibaut Bourdais, Nadia Oudjane, Francesco Russo
In this paper, we propose an original approach to stochastic control problems. We consider a weak formulation that is written as an optimization (minimization) problem on the space…
Reimagining Demand-Side Management with Mean Field Learning
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard +1
Integrating renewable energy into the power grid while balancing supply and demand is a complex issue, given its intermittent nature. Demand side management (DSM) offers solutions…
Does 3D frequency-domain FWI of full-azimuth/long-offset OBN data feasible? The Gorgon case study
S. Operto, P. Amestoy, H. S. Aghamiry +13
Frequency-domain Full Waveform Inversion (FWI) is potentially amenable to efficient processing of full-azimuth long-offset stationary-recording seabed acquisition carried out with…
A simple city equilibrium model with an application to teleworking
Yves Achdou, Guillaume Carlier, Quentin Petit +1
We propose a simple semi-discrete spatial model where rents, wages and the density of population in a city can be deduced from free-mobility and equilibrium conditions on the labou…
Multi-stage Stochastic Alternating Current Optimal Power Flow with Storage: Bounding the Relaxation Gap
Maxime Grangereau, Wim van Ackooij, Stéphane Gaubert
We propose a generic multistage stochastic model for the Alternating Current Optimal Power Flow (AC OPF) problem for radial distribution networks, to account for the random electri…
Chance constrained problems: a bilevel convex optimization perspective
Yassine Laguel, Jérôme Malick, Wim Ackooij
Chance constraints are a valuable tool for the design of safe decisions in uncertain environments; they are used to model satisfaction of a constraint with a target probability. Ho…
On the Convexity of Level-sets of Probability Functions
Yassine Laguel, Wim van Ackooij, Jérôme Malick +1
In decision-making problems under uncertainty, probabilistic constraints are a valuable tool to express safety of decisions. They result from taking the probability measure of a gi…
Neural networks-based algorithms for stochastic control and PDEs in finance
Maximilien Germain, Huyên Pham, Xavier Warin
This paper presents machine learning techniques and deep reinforcement learningbased algorithms for the efficient resolution of nonlinear partial differential equations and dynamic…
Hierarchical coupled routing-charging model of electric vehicles, stations and grid operators
Benoît Sohet, Yezekael Hayel, Olivier Beaude +1
Electric Vehicles' (EVs) growing number has various consequences, from reducing greenhouse gas emissions and local pollution to altering traffic congestion and electricity consumpt…
Decomposition of convex high dimensional aggregative stochasticcontrol problems
Adrien Séguret, Clémence Alasseur, J. Frédéric Bonnans +3
We consider the framework of convex high dimensional stochastic control problems, in which the controls are aggregated in the cost function. As first contribution, we introduce a m…
Logarithmic regret for episodic continuous-time linear-quadratic reinforcement learning over a finite-time horizon
Matteo Basei, Xin Guo, Anran Hu +1
We study finite-time horizon continuous-time linear-quadratic reinforcement learning problems in an episodic setting, where both the state and control coefficients are unknown to t…
Demand Side Management in the Smart Grid: an Efficiency and Fairness Tradeoff
Paulin Jacquot, Olivier Beaude, Stéphane Gaubert +1
We compare two Demand Side Management (DSM) mechanisms, introduced respectively by Mohsenian-Rad et al (2010) and Baharlouei et al (2012), in terms of efficiency and fairness. Each…
Log-barrier interior point methods are not strongly polynomial
Xavier Allamigeon, Pascal Benchimol, Stéphane Gaubert +1
We prove that primal-dual log-barrier interior point methods are not strongly polynomial, by constructing a family of linear programs with inequalities in dimension for…
Some non monotone schemes for time dependent Hamilton-Jacobi-Bellman equations in stochastic control
Xavier Warin
We introduce some approximation schemes for linear and fully non-linear diffusion equations of Bellman-Isaacs type. Although they are not monotone one can prove their convergence t…
Price decomposition in large-scale stochastic optimal control
Kengy Barty, Pierre Carpentier, Guy Cohen +1
We are interested in optimally driving a dynamical system that can be influenced by exogenous noises. This is generally called a Stochastic Optimal Control (SOC) problem and the Dy…