The Crew Pairing Problem (CPP) involves constructing feasible pairings (sequences of flights, connections, and rest periods) for airline crew while minimizin...

Origin--destination (OD) matrices are essential for forecasting and capacity planning in transportation and communication networks, yet they are not directl...

Large-scale distributed wireless networks offer infrastructure-free and cost-effective connectivity. Recent theoretical work has shown that scalability crit...

Distributed wireless networks provide scalable and decentralized connectivity for applications ranging from IoT and vehicular communication to emergency resp...

Designing icephobic surfaces to delay ice formation is crucial for applications like aviation safety and cryopreservation. While Classical Nucleation Theory ...

This work studies constrained blackbox optimization problems that cannot be solved in reasonable time due to prohibitive computational costs. This challenge...

Bus scheduling problem is a core optimization problem for public transit agencies. Given a set of timetabled trips to cover during a day and a homogeneous bu...

Benchmarking new optimization methods on test problems is essential for assessing their performance and tuning their parameters. Yet, few problems are avail...

This paper presents a transmission expansion planning framework that couples Benders decomposition with an operational layer based on a semidefinite programm...

This paper investigates the Collaborative Routing Orchestration for Organic Food Distribution Problem (CRO-FDP), a two-echelon collaborative distribution n...

The CRM, IVADO, and GERAD organized jointly the Fifteenth Montreal Industrial Problem Solving Workshop, which was held at HEC Montréal on June 2-6, 2025. We ...

In this paper, we study the pickup and delivery problem with time windows, multiple compartments, incompatibility constraints and cleaning operations (PDPTWM...

This paper presents RegularizedOptimization.jl, a Julia package that implements families of nonsmooth optimization methods.

We develop R2N, a modified quasi-Newton method for minimizing the sum of a \(\mathcal{C}^1\) function \(f\) and a lower semi-continuous prox-bounded `(h...

We extend traditional complexity analyses of trust-region methods for unconstrained, possibly nonconvex, optimization. Whereas most complexity analyses assu...

We develop a worst-case evaluation complexity bound for trust-region methods in the presence of unbounded Hessian approximations. We use the algorithm of ...

We introduce method iR2N, a modified proximal quasi-Newton method for minimizing the sum of a \(\mathcal{C}^1\) function \(f\) and a lower semi-continuou...

This work presents a case study where four well-known derivative-free solvers are benchmarked on several instances based on the \(\textsf{solar}\) suite of...

Effective waste rock management is a crucial aspect of long-term mine planning and production scheduling. When waste management is not considered during th...

The reformulation-linearization technique (RLT) is a well-established framework for generating hierarchies of linear programming (LP) relaxations for a wide ...