Improving neural network optimizer convergence speed is a long-standing priority. Recently, there has been a focus on quasi-Newton optimization methods, whi...

Benders decomposition has been applied significantly to tackle large-scale optimization problems with complicating variables, which, when temporarily fixed, ...

Historically, the training of deep artificial neural networks has relied on parallel computing to achieve practical effectiveness. However, with the increas...

We introduce an iterative solver named MINARES for symmetric linear systems $Ax \approx b$, where $A$ is possibly singular. MINARES is based on t...

Operations research specialists at the OCP Group, the Mohammed VI Polytechnic University, and the Polytechnique Montreal operationalized a system optimizing ...

Decision trees are highly interpretable models for solving classification problems in machine learning (ML). The standard ML algorithms for training decision...

We introduce a variant of the proximal gradient method in which the quadratic term is diagonal but may be indefinite, and is safeguarded by a trust region. ...

Tactical wireless networks are used in cases where standard telecommunication networks are unavailable or unusable, e.g. disaster relief operations. We fully...

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...

Perturbations are universal in supply chains, and their appearance is getting more frequent in the past few years. These perturbations affect industries and ...

This paper presents a study on the best possible use of optimization models for the short-term hydropower scheduling problem. Different deterministic and sto...

This paper develops an efficient hybrid algorithm to solve the credit scoring problem. We use statistical mathematical programming to develop new classificat...

The emerging demand for electric bicycles in recent years has prompted several bike-sharing systems (BSS) around the world to adapt their service to a new wa...

The popularity of bike-sharing systems has constantly increased throughout the last years. Most of such success can be attributed to their multiple benefits,...

We consider the problem of minimizing the linear cost of multistate homogeneous series-parallel system given the nonlinear reliability constraint on the syst...

In this paper, we study the pickup and delivery problem with time windows and multiple compartments (PDPTWMC). The PDPTWMC generalizes the pickup and delive...

To cover the import taxes, a manufacturer typically charges a higher price in a foreign market than in its domestic market. The price difference can lead to ...

This paper presents <code>FluxNLPModels.jl</code> and <code>KnetNLPModels.jl</code>, new Julia packages enabling a neural network, modelled with either Flux....

The Quadratic Knapsack Problem (QKP) is a combinatorial optimization problem that has attracted much attention over the past four decades. In this problem, o...

Recently there has been a surge of interest in operations research~(OR) and the machine learning~(ML) community in combining prediction algorithms and optimi...