249 citations · 790 across the 59 of their papers we have counts for
22 papers · 1 filter
Assortment Optimization with Visibility Constraints
Theo Barre, Omar El Housni, Marouane Ibn Brahim +2
Motivated by applications in e-retail and online advertising, we study the problem of assortment optimization under visibility constraints, that we refer to as APV. Here, we are gi…
Integer Programming Games: A Gentle Computational Overview
Margarida Carvalho, Gabriele Dragotto, Andrea Lodi +1
In this tutorial, we present a computational overview on computing Nash equilibria in Integer Programming Games (s), , how to compute solutions for a class of non-cooper…
Operational Research: Methods and Applications
Fotios Petropoulos, Gilbert Laporte, Emel Aktas +79
Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This…
The Critical Node Game
Gabriele Dragotto, Amine Boukhtouta, Andrea Lodi +1
In this work, we introduce a game-theoretic model that assesses the cyber-security risk of cloud networks and informs security experts on the optimal security strategies. Our appro…
Recovering Dantzig-Wolfe Bounds by Cutting Planes
Rui Chen, Oktay Gunluk, Andrea Lodi
Dantzig-Wolfe (DW) decomposition is a well-known technique in mixed-integer programming (MIP) for decomposing and convexifying constraints to obtain potentially strong dual bounds.…
A machine learning framework for neighbor generation in metaheuristic search
Defeng Liu, Vincent Perreault, Alain Hertz +1
This paper presents a methodology for integrating machine learning techniques into metaheuristics for solving combinatorial optimization problems. Namely, we propose a general mach…
A Framework for Fair Decision-making Over Time with Time-invariant Utilities
Andrea Lodi, Sriram Sankaranarayanan, Guanyi Wang
Fairness is a major concern in contemporary decision problems. In these situations, the objective is to maximize fairness while preserving the efficacy of the underlying decision-m…
Learning to repeatedly solve routing problems
Mouad Morabit, Guy Desaulniers, Andrea Lodi
In the last years, there has been a great interest in machine-learning-based heuristics for solving NP-hard combinatorial optimization problems. The developed methods have shown po…
Online Decision Making with Fairness over Time
Rui Chen, Oktay Gunluk, Andrea Lodi +1
Online platforms increasingly rely on sequential decision-making algorithms to allocate resources, match users, or control exposure, while facing growing pressure to ensure fairnes…
Fast Continuous and Integer L-shaped Heuristics Through Supervised Learning
Eric Larsen, Emma Frejinger, Bernard Gendron +1
We propose a methodology at the nexus of operations research and machine learning (ML) leveraging generic approximators available from ML to accelerate the solution of mixed-intege…
Continuous cutting plane algorithms in integer programming
Didier Chételat, Andrea Lodi
Cutting planes for mixed-integer linear programs (MILPs) are typically computed in rounds by iteratively solving optimization problems, the so-called separation. Instead, we refram…
Machine-learning-based arc selection for constrained shortest path problems in column generation
Mouad Morabit, Guy Desaulniers, Andrea Lodi
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 one or more pricing probl…
The Cut-and-Play Algorithm: Computing Nash Equilibria via Outer Approximations
Margarida Carvalho, Gabriele Dragotto, Andrea Lodi +1
We introduce Cut-and-Play, a practically-efficient algorithm for computing Nash equilibria in simultaneous non-cooperative games where players decide via nonconvex and possibly unb…
An Exact Method for (Constrained) Assortment Optimization Problems with Product Costs
Markus Leitner, Andrea Lodi, Roberto Roberti +1
We study the problem of optimizing assortment decisions in the presence of product-specific costs when customers choose according to a multinomial logit model. This problem is NP-h…
Cardinality Minimization, Constraints, and Regularization: A Survey
Andreas M. Tillmann, Daniel Bienstock, Andrea Lodi +1
We survey optimization problems that involve the cardinality of variable vectors in constraints or the objective function. We provide a unified viewpoint on the general problem cla…
Reinforcement Learning for Freight Booking Control Problems
Justin Dumouchelle, Emma Frejinger, Andrea Lodi
Booking control problems are sequential decision-making problems that occur in the domain of revenue management. More precisely, freight booking control focuses on the problem of d…
Fairness over time in dynamic resource allocation with an application in Healthcare
Andrea Lodi, Philippe Olivier, Gilles Pesant +1
Decision making problems are typically concerned with maximizing efficiency. In contrast, we address problems where there are multiple stakeholders and a centralized decision maker…
Design and implementation of a modular interior-point solver for linear optimization
Miguel F. Anjos, Andrea Lodi, Mathieu Tanneau
This paper introduces the algorithmic design and implementation of Tulip, an open-source interior-point solver for linear optimization. It implements a regularized homogeneous inte…
A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs
Yoshua Bengio, Emma Frejinger, Andrea Lodi +2
We propose a novel approach using supervised learning to obtain near-optimal primal solutions for two-stage stochastic integer programming (2SIP) problems with constraints in the f…
Disjunctive cuts in Mixed-Integer Conic Optimization
Andrea Lodi, Mathieu Tanneau, Juan Pablo Vielma
This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for separating disjunctive…
On Generalized Surrogate Duality in Mixed-Integer Nonlinear Programming
Benjamin Müller, Gonzalo Muñoz, Maxime Gasse +3
The most important ingredient for solving mixed-integer nonlinear programs (MINLPs) to global epsilon-optimality with spatial branch and bound is a tight, computationally tractable…
Learning to Handle Parameter Perturbations in Combinatorial Optimization: an Application to Facility Location
Andrea Lodi, Luca Mossina, Emmanuel Rachelson
We present an approach to couple the resolution of Combinatorial Optimization problems with methods from Machine Learning, applied to the single source, capacitated, facility locat…