In this work, we study a class of two-player deterministic finite-horizon difference games with coupled inequality constraints, where both players have two t...

In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...

We consider the set of graphs that can be constructed from a one-vertex graph by repeatedly adding a clique or a stable set linked to all or none of the vert...

Incentive-based demand response aggregators are widely recognized as a powerful strategy to increase the flexibility of residential community microgrid (RCM)...

Recommender systems provide personalized recommendations to their users for items and services. They do that using a model that is tailored to each user to i...

We propose new algorithms with provable performance for online binary optimization subject to general constraints and in dynamic settings. We consider the su...

In this paper, a new model is proposed for the real-time diesel genset optimal dispatch and unit commitment in remote microgrids. The objective is to reduce ...

Le Douzième atelier de résolution de problèmes industriels de Montréal, qui eut lieu du 22 au 26 août 2022, fut organisé conjointement par le Centre de reche...

An innovative simultaneous stochastic optimization approach is proposed that combines actor-critic reinforcement learning and stochastic mathematical progr...

In multi-robot missions, relative position and attitude information between robots is valuable for a variety of tasks such as mapping, planning, and formatio...

Recommender systems provide recommendations to their users for items and services by creating a model tailored to each user to infer their preferences based ...

Motivated by our collaboration with one of the largest fast-fashion retailers in Europe, we study a two-echelon inventory control problem called the One-Ware...

We consider online optimization problems with time-varying linear equality constraints. In this framework, an agent makes sequential decisions using only pri...

La plupart des méthodes d'apprentissage par renforcement pour le contrôle adaptatif de la signalisation routière nécessitent une formation partant de zéro po...

Les systèmes de production d'énergie renouvelables hybrides (SPERH), où l'on peut trouver deux ou plusieurs moyens de production d'énergie renouvelables co-l...

Les charges thermostatiques, telles que le chauffage électrique de l'eau et des bâtiments, ont un impact significatif sur la demande en électricité sur une a...

Le Dixième atelier de résolution de problèmes industriels de Montréal, qui eut lieu du 13 au 27 août 2020, fut organisé conjointement par le Centre de recher...

This paper studies a stochastic variant of the vehicle routing problem (VRP) where both customer locations and demands are uncertain. In particular, potentia...

The existing technologies that update geostatistically simulated models of mineral deposits cannot self-learn from incoming new information generated in oper...

A new mathematical model for stochastic short-term optimization of mining complexes is presented that simultaneously optimizes the short-term extraction sequ...