Andrea Lodi

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

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

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

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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...

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

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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...

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

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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...

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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...

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

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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...

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

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

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

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

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

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

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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...

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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...

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

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