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 ...

The Twelfth Montreal IPSW took place on August 22-26, 2022, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for D...

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...

Most reinforcement learning methods for adaptive-traffic-signal-control require training from scratch to be applied on any new intersection or after any modi...

Hybrid renewable energy systems (HRES), which co-locate two or more renewable energy sources, have proven to be promising frameworks for harnessing complemen...

Thermostatically-controlled loads have a significant impact on electricity demand after service is restored following an outage, a phenomenon known as cold l...

The Tenth Montreal IPSW took place on August 13-27, 2020, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for Dat...

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...

Personnel scheduling consists of determining least-cost work schedules to cover the demand of multiple jobs expressed in number of employees per job and peri...

In this paper, we study the competition between national brands and private labels (or store brands) by analyzing the impacts of their presence on strategies...

Microgrid, a promising component of smart grid, will potentially yield a free electricity market. This paper proposes a novel construction for a community mi...

The Integral Simplex Using Decomposition (ISUD) algorithm has been developed recently to solve large set partitioning problems (SPPs) in a primal way, i.e.,...