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DOI: 10.4121/0b943091-fcc4-4acb-920a-a1080b8790b3

Julien, Esther (2025): Datasets for the dissertation "Leveraging Data in Algorithm Design". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0b943091-fcc4-4acb-920a-a1080b8790b3.v1

Categories

• Applied Mathematics
• Evolutionary Biology
• Mathematical Sciences
• Biological Sciences

Keywords

Algorithms Bilevel Optimization Cherry Picking Data-Driven Algorithms Discrete Optimization Heuristics Machine Learning Operations Research Phylogenetics Robust Optimization

Licence

CC BY 4.0

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by Esther Julien

The contents of this repository are the source code and datasets for each of the chapters of the dissertation by Esther Julien. This dissertation explores the use of machine-learning techniques to improve the performance of various algorithms. These algorithms solve problems appearing within the field of operations research, with a focus on bilevel optimization and adaptable robust optimization, and for the construction of phylogenetic networks. The data consists of source code for each of these projects and data for test instances and self-generated training data for the various supervised machine-learning models.

History

• 2025-02-21 first online, published, posted

Publisher

4TU.ResearchData

Format

.py for source code/ .txt for instance data/ .csv for results/ .pkl (pickle file) for data/ .joblib for trained random forest models

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft Institute of Applied Mathematics