268 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de MontréalCA14 papers
- Polytechnique MontréalCA10 papers
- McGill UniversityCA5 papers
- Mila - Quebec Artificial Intelligence InstituteCA4 papers
- Cornell TechUS2 papers
- INESC TECPT2 papers
- Pontifícia Universidade Católica do Rio de JaneiroBR2 papers
- Universidade do PortoPT2 papers
- Cornell UniversityUS1 paper
- Département d'InformatiqueFR1 paper
- Group for Research in Decision AnalysisCA1 paper
- Hydro-QuébecCA1 paper
19 papers
Asymmetry in the Complexity of the Multi-Commodity Network Pricing Problem
Quang Minh Bui, Margarida Carvalho, José Neto
The network pricing problem (NPP) is a bilevel problem, where the leader optimizes its revenue by deciding on the prices of certain arcs in a graph, while expecting the followers (…
A stochastic integer programming approach to reserve staff scheduling with preferences
Carl Perreault-Lafleur, Margarida Carvalho, Guy Desaulniers
Nowadays, reaching a high level of employee satisfaction in efficient schedules is an important and difficult task faced by companies. We tackle a new variant of the personnel sche…
Bayesian calibration of traffic flow fundamental diagrams using Gaussian processes
Zhanhong Cheng, Xudong Wang, Xinyuan Chen +2
Modeling the relationship between vehicle speed and density on the road is a fundamental problem in traffic flow theory. Recent research found that using the least-squares (LS) met…
Adaptation, Comparison and Practical Implementation of Fairness Schemes in Kidney Exchange Programs
William St-Arnaud, Margarida Carvalho, Golnoosh Farnadi
In Kidney Exchange Programs (KEPs), each participating patient is registered together with an incompatible donor. Donors without an incompatible patient can also register. Then, KE…
Optimising Electric Vehicle Charging Station Placement using Advanced Discrete Choice Models
Steven Lamontagne, Margarida Carvalho, Emma Frejinger +3
We present a new model for finding the optimal placement of electric vehicle charging stations across a multi-period time frame so as to maximise electric vehicle adoption. Via the…
A Catalog of Formulations for the Network Pricing Problem
Quang Minh Bui, Bernard Gendron, Margarida Carvalho
We study the network pricing problem where the leader maximizes their revenue by determining the optimal amounts of tolls to charge on a set of arcs, under the assumption that the…
Real-time forecasting of metro origin-destination matrices with high-order weighted dynamic mode decomposition
Zhanhong Cheng, Martin Trepanier, Lijun Sun
Forecasting the short-term ridership among origin-destination pairs (OD matrix) of a metro system is crucial in real-time metro operation. However, this problem is notoriously diff…
Computing Nash equilibria for integer programming games
Margarida Carvalho, Andrea Lodi, João Pedro Pedroso
The recently defined class of integer programming games (IPG) models situations where multiple self-interested decision makers interact, with their strategy sets represented by a f…
Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood
Thibaut Vidal
The vehicle routing problem is one of the most studied combinatorial optimization topics, due to its practical importance and methodological interest. Yet, despite extensive method…
Incorporating travel behavior regularity into passenger flow forecasting
Zhanhong Cheng, Martin Trepanier, Lijun Sun
Accurate forecasting of passenger flow (i.e., ridership) is critical to the operation of urban metro systems. Previous studies mainly model passenger flow as time series by aggrega…
Segmentation and Optimal Region Selection of Physiological Signals using Deep Neural Networks and Combinatorial Optimization
Jorge Oliveira, Margarida Carvalho, Diogo Marcelo Nogueira +1
Physiological signals, such as the electrocardiogram and the phonocardiogram are very often corrupted by noisy sources. Usually, artificial intelligent algorithms analyze the signa…
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming
Mostafa ElAraby, Guy Wolf, Margarida Carvalho
We introduce a mixed integer program (MIP) for assigning importance scores to each neuron in deep neural network architectures which is guided by the impact of their simultaneous p…
Game theoretical analysis of Kidney Exchange Programs
Margarida Carvalho, Andrea Lodi
The goal of a kidney exchange program (KEP) is to maximize number of transplants within a pool of incompatible patient-donor pairs by exchanging donors. A KEP can be modelled as a…
When Nash Meets Stackelberg
Margarida Carvalho, Gabriele Dragotto, Felipe Feijoo +2
This article introduces a class of games among players (), namely, a class of simultaneous non-cooperative games where the players solve sequential Stac…
Bayesian Temporal Factorization for Multidimensional Time Series Prediction
Xinyu Chen, Lijun Sun
Large-scale and multidimensional spatiotemporal data sets are becoming ubiquitous in many real-world applications such as monitoring urban traffic and air quality. Making predictio…
Strong Bounds for Resource Constrained Project Scheduling: Preprocessing and Cutting Planes
Janniele A. S. Araujo, Haroldo Gambini Santos, Bernard Gendron +3
Resource Constrained Project Scheduling Problems (RCPSPs) without preemption are well-known NP-hard combinatorial optimization problems. A feasible RCPSP solution consists of a tim…
Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
Eric Larsen, Sébastien Lachapelle, Yoshua Bengio +3
This paper offers a methodological contribution at the intersection of machine learning and operations research. Namely, we propose a methodology to quickly predict tactical soluti…
Industrial and Tramp Ship Routing Problems: Closing the Gap for Real-Scale Instances
Gabriel Homsi, Rafael Martinelli, Thibaut Vidal +1
Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo…
Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
Eric Larsen, Sébastien Lachapelle, Yoshua Bengio +3
This paper offers a methodological contribution at the intersection of machine learning and operations research. Namely, we propose a methodology to quickly predict expected tactic…