118 citations · 146 across the 6 of their papers we have counts for
9 papers
Decision-focused predictions via pessimistic bilevel optimization: complexity and algorithms
Víctor Bucarey, Sophia Calderón, Gonzalo Muñoz +1
Dealing with uncertainty in optimization parameters is an important and longstanding challenge. Typically, uncertain parameters are predicted accurately, and then a deterministic o…
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
Jayanta Mandi, James Kotary, Senne Berden +4
Decision-focused learning (DFL) is an emerging paradigm that integrates machine learning (ML) and constrained optimization to enhance decision quality by training ML models in an e…
Probability estimation and structured output prediction for learning preferences in last mile delivery
Rocsildes Canoy, Victor Bucarey, Yves Molenbruch +3
We study the problem of learning the preferences of drivers and planners in the context of last mile delivery. Given a data set containing historical decisions and delivery locatio…
Decision-Focused Learning: Through the Lens of Learning to Rank
Jayanta Mandi, Víctor Bucarey, Maxime Mulamba +1
In the last years decision-focused learning framework, also known as predict-and-optimize, have received increasing attention. In this setting, the predictions of a machine learnin…
Data Driven VRP: A Neural Network Model to Learn Hidden Preferences for VRP
Jayanta Mandi, Rocsildes Canoy, Víctor Bucarey +1
The traditional Capacitated Vehicle Routing Problem (CVRP) minimizes the total distance of the routes under the capacity constraints of the vehicles. But more often, the objective…
Learn-n-Route: Learning implicit preferences for vehicle routing
Rocsildes Canoy, Víctor Bucarey, Jayanta Mandi +1
We investigate a learning decision support system for vehicle routing, where the routing engine learns implicit preferences that human planners have when manually creating route pl…
An exact dynamic programming approach to segmented isotonic regression
Víctor Bucarey, Martine Labbé, Juan M. Morales +1
This paper proposes a polynomial-time algorithm to construct the monotone stepwise curve that minimizes the sum of squared errors with respect to a given cloud of data points. The…
Contrastive Losses and Solution Caching for Predict-and-Optimize
Maxime Mulamba, Jayanta Mandi, Michelangelo Diligenti +3
Many decision-making processes involve solving a combinatorial optimization problem with uncertain input that can be estimated from historic data. Recently, problems in this class…
Benders decomposition for Network Design Covering Problems
Víctor Bucarey, Bernard Fortz, Natividad González-Blanco +2
We consider two covering variants of the network design problem. We are given a set of origin/destination pairs, called O/D pairs, and each such O/D pair is covered if there exists…