Station-based Bike-sharing systems have been implemented in multiple major cities, offering a low-cost and environmentally friendly transportation alternativ...

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

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

The multi-depot scheduling problem (MDVSP) is one of the most studied problem in public transport service planning. It consists of assigning buses to each ti...

We consider the problem of training a deep neural network with nonsmooth regularization to retrieve a sparse and efficient sub-structure. Our regularizer is ...

Column generation is an iterative method used to solve a variety of optimization problems. It decomposes the problem into two parts: a master problem, and on...

In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning. In the first-orde...

Drones have been getting more and more popular in many economy sectors. Both scientific and industrial communities aim at making the impact of drones even mo...

We propose a new stochastic variance-reduced damped L-BFGS algorithm, where we leverage estimates of bounds on the largest and smallest eigenvalues of the He...

This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for...

Column generation (CG) is widely used for solving large-scale optimization problems. This article presents a new approach based on a machine learning (ML) t...

Artificial Intelligence (AI) is the next society transformation builder. Massive AI-based applications include cloud servers, cell phones, cars, and pandemic...

The popularity of drones is rapidly increasing across the different sectors of the economy. Aerial capabilities and relatively low costs make drones the perf...

A highly influential ingredient of many techniques designed to exploit sparsity in numerical optimization is the so-called chordal extension of a graph repre...

This paper introduces the algorithmic design and implementation of Tulip, an open-source interior-point solver for linear optimization. It implements the ho...

In this paper, we develop algorithmic approaches for a recently defined class of games, the integer programming games. Two general methods to approximate an...

This paper addresses combinatorial optimization problems under uncertain and correlated data where the mean-covariance information of the random data is assu...

In this paper we consider a version of the capacitated vehicle routing problem (CVRP) where travel times are assumed to be uncertain and statistically corre...

Within state-of-the-art optimization solvers such as IBM--CPLEX the ability to solve both convex and nonconvex Mixed-Integer Quadratic Programming (MIQP) pro...

The integral simplex using decomposition (ISUD) algorithm <font size=2>[Zaghrouti, A., Soumis, F., Elhallaoui, I.: Integral simplex using decomposition for t...