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Found 5 papers, 1 papers with code
An improved column-generation-based matheuristic for learning classification trees
This approach improves scalability and can work with large datasets.
Learning to repeatedly solve routing problems
This partial prediction of the solution reduces the complexity of the problem and speeds up its resolution, while yielding a good quality solution.
Explainable prediction of Qcodes for NOTAMs using column generation
A NOtice To AirMen (NOTAM) contains important flight route related information.
Machine-learning-based arc selection for constrained shortest path problems in column generation
Column generation is an iterative method used to solve a variety of optimization problems.
Predicting the probability distribution of bus travel time to move towards reliable planning of public transport services
Two types of probabilistic models, namely similarity-based density estimation models and a smoothed Logistic Regression for probabilistic classification model, are compared on a dataset of more than 41, 000 trips and 50 bus routes of the city of Montr\'eal.
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