37 citations · 139 across the 35 of their papers we have counts for
16 papers · 1 filter
Copositive Characterizations of Convex Hull Pricing
Madhusudan Ghosh, Antoine Lesage-Landry, Joshua Adam Taylor
Due to the nonconvex binary constraints of unit commitment (UC), no uniform linear pricing scheme supports the optimal dispatch. Convex hull pricing (CHP) and copositive duality pr…
Parallel versions of the mesh adaptive direct search algorithm
Sébastien Le Digabel, Antoine Lesage-Landry, Samuel Mendoza +1
This work surveys the different parallel variants of the mesh adaptive direct search (MADS) algorithm for constrained blackbox optimization. These problems can inherently imply hig…
Online Sketched Newton-Raphson
Jean-Luc Lupien, Yuen-Man Pun, Youssef Diouane +2
In online convex optimization (OCO), a decision-maker is confronted with an unknown environment and seeks to play an optimal sequence of decisions on a short time-scale using only…
Distributed Combined Space Partitioning and Network Flow Optimization: an Optimal Transport Approach (Extended Version)
Théo Laurentin, Patrick Coirault, Emmanuel Moulay +2
This paper studies a combined space partitioning and network flow optimization problem, with applications to large-scale power, transportation, or communication systems. In dense w…
Efficient search strategies for constrained multiobjective blackbox optimization
Sébastien Le Digabel, Antoine Lesage-Landry, Ludovic Salomon +1
Multiobjective blackbox optimization deals with problems where the objective and constraint functions are the outputs of a numerical simulation. In this context, no derivatives are…
Min-Max Optimisation for Nonconvex-Nonconcave Functions Using a Random Zeroth-Order Extragradient Algorithm
Amir Ali Farzin, Yuen Man Pun, Philipp Braun +3
This study explores the performance of the random Gaussian smoothing Zeroth-Order ExtraGradient (ZO-EG) scheme considering \Af{deterministic} min-max optimisation problems with pos…
Ex Post Conditions for the Exactness of Optimal Power Flow Conic Relaxations
Jean-Luc Lupien, Antoine Lesage-Landry
Convex relaxations of the optimal power flow (OPF) problem provide an efficient alternative to solving the intractable alternating current (AC) optimal power flow. The conic subset…
Online Interior-point Methods for Time-varying Equality-constrained Optimization
Jean-Luc Lupien, Iman Shames, Antoine Lesage-Landry
An important challenge in the online convex optimization (OCO) setting is to incorporate generalized inequalities and time-varying constraints. The inclusion of constraints in OCO…
Online Dynamic Submodular Optimization
Antoine Lesage-Landry, Julien Pallage
We propose new algorithms with provable performance for online binary optimization subject to general constraints and in dynamic settings. We consider the subset of problems in whi…
An Online Newton's Method for Time-varying Linear Equality Constraints
Jean-Luc Lupien, Antoine Lesage-Landry
We consider online optimization problems with time-varying linear equality constraints. In this framework, an agent makes sequential decisions using only prior information. At ever…
Optimally Scheduling Public Safety Power Shutoffs
Antoine Lesage-Landry, Félix Pellerin, Joshua A. Taylor +1
In an effort to reduce power system-caused wildfires, utilities carry out public safety power shutoffs (PSPS) in which portions of the grid are de-energized to mitigate the risk of…
Online Convex Optimization with Binary Constraints
Antoine Lesage-Landry, Joshua A. Taylor, Duncan S. Callaway
We consider online optimization with binary decision variables and convex loss functions. We design a new algorithm, binary online gradient descent (bOGD) and bound its expected dy…
Dynamic and Distributed Online Convex Optimization for Demand Response of Commercial Buildings
Antoine Lesage-Landry, Duncan S. Callaway
We extend the regret analysis of the online distributed weighted dual averaging (DWDA) algorithm [1] to the dynamic setting and provide the tightest dynamic regret bound known to d…
Second-order Online Nonconvex Optimization
Antoine Lesage-Landry, Joshua A. Taylor, Iman Shames
We present the online Newton's method, a single-step second-order method for online nonconvex optimization. We analyze its performance and obtain a dynamic regret bound that is lin…
Predictive Online Convex Optimization
Antoine Lesage-Landry, Iman Shames, Joshua A. Taylor
We incorporate future information in the form of the estimated value of future gradients in online convex optimization. This is motivated by demand response in power systems, where…
Setpoint Tracking with Partially Observed Loads
Antoine Lesage-Landry, Joshua A. Taylor
We use online convex optimization (OCO) for setpoint tracking with uncertain, flexible loads. We consider full feedback from the loads, bandit feedback, and two intermediate types…