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Found 7 papers, 6 papers with code
Neur2BiLO: Neural Bilevel Optimization
Bilevel optimization deals with nested problems in which a leader takes the first decision to minimize their objective function while accounting for a follower's best-response reaction.
Neur2RO: Neural Two-Stage Robust Optimization
This work addresses two-stage robust optimization (2RO) problems (also called adjustable robust optimization), wherein first-stage and second-stage decisions are made before and after uncertainty is realized, respectively.
Neur2SP: Neural Two-Stage Stochastic Programming
Stochastic Programming is a powerful modeling framework for decision-making under uncertainty.
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
Combinatorial optimization is a well-established area in operations research and computer science.
Ecole: A Library for Learning Inside MILP Solvers
In this paper we describe Ecole (Extensible Combinatorial Optimization Learning Environments), a library to facilitate integration of machine learning in combinatorial optimization solvers.
Reinforcement Learning for Freight Booking Control Problems
Routinely solving such operational problems when deploying reinforcement learning algorithms may be too time consuming.
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers
We present Ecole, a new library to simplify machine learning research for combinatorial optimization.
