JuliaDecisionFocusedLearning/DecisionFocusedLearningBenchmarks.jl

Benchmark problems for decision-focused learning

37
/ 100
Emerging

This collection helps researchers and practitioners in optimization and machine learning evaluate and compare different Decision-Focused Learning (DFL) algorithms. It provides standardized datasets, statistical models, and combinatorial optimizers that can be fed into any DFL training algorithm. It is for those who are developing or testing DFL approaches.

Use this if you need pre-built, diverse problem settings to rigorously test and benchmark the performance of new or existing Decision-Focused Learning algorithms.

Not ideal if you are looking for a standalone DFL solution to a specific real-world problem, rather than a toolkit for algorithm evaluation.

operations-research machine-learning-research optimization-algorithms algorithm-benchmarking predictive-optimization
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 5 / 25

How are scores calculated?

Stars

15

Forks

1

Language

Julia

License

MIT

Last pushed

Mar 12, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/JuliaDecisionFocusedLearning/DecisionFocusedLearningBenchmarks.jl"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.