This work introduces a _partitioned optimization framework_ (POf) to ease the solving process for optimization problems for which fixing some variables to a...

This paper addresses the limitations of current satellite payload architectures, which are predominantly hardware-driven and lack the flexibility to adapt to...

This paper tackles a complex variant of the unit commitment (UC) problem at Hydro-Quebec, referred to as the transient stability constrained unit commitmen...

This paper introduces a new step to the Direct Search Method (DSM) to strengthen its convergence analysis. By design, this so-called covering step may e...

We describe the implementation of RipQP, an interior-point algorithm for convex quadratic optimization. Our Julia implementation is open source, and accommo...

This work introduces solar, a collection of ten optimization problem instances for benchmarking blackbox optimization solvers. The instances present differ...

The aim of this paper is to analyze the effect of adaptive investments on international environmental agreements (IEAs) focused on reducing greenhouse gas ...

Heterogeneous datasets emerge in various machine learning or optimization applications that feature different data sources, various data types and complex re...

Randomized algorithms have proven to perform well on a large class of numerical linear algebra problems. Their theoretical analysis is critical to provide gu...

Augmented Lagrangian (AL) methods are a well known class of algorithms for solving constrained optimization problems. They have been extended to the solution...

Transit authorities are rapidly replacing conventional buses with electric ones because of the increasing concerns about air quality, greenhouse gas emission...

The Thirteenth Montreal IPSW took place on August 21-25, 2023, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute ...

This paper describes a planning problem faced by a fast-growing petroleum company in West Africa. The problem is a complex variant of the petrol station repl...

Efficiently solving a vehicle routing problem ($\mathcal{VRP}$) in a practical runtime is a critical challenge for delivery management companies. This pa...

This poster conceptually lays out recent advances in trustworthy machine learning (ML) that are of great interest for power systems applications like virtu...

The truck loading and inventory routing problems are the two most important decisions made by companies replenishing petrol stations. This paper investigates...

The purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...

We develop a trust-region method for minimizing the sum of a smooth term $f$ and a nonsmooth term $h$, both of which can be nonconvex. Each iteratio...

We develop an interior-point method for nonsmooth regularized bound-constrained optimization problems. Our method consists of iteratively solving a sequence...

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...