mlsanityData to 7 Oct 2026

Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers

arXiv 2011.06069 ↗First posted 11 Nov 2020cs.LG math.OCcited by 43

Not on the map. Why?

Abstract (arXiv)

We present Ecole, a new library to simplify machine learning research for combinatorial optimization. Ecole exposes several key decision tasks arising in general-purpose combinatorial optimization solvers as control problems over Markov decision processes. Its interface mimics the popular OpenAI Gym library and is both extensible and intuitive to use. We aim at making this library a standardized platform that will lower the bar of entry and accelerate innovation in the field. Documentation and code can be found at https://www.ecole.ai.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Nov 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 10; 2023: 9; 2024: 10; 2025: 6; 2026: 7.

43 papers.

Sort:

By area:

  1. 2021Combinatorial optimization and reasoning with graph neural networkscited by 267
  2. 2023RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmarkcited by 70
  3. 2022Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learningcited by 58
  4. 2024RouteFinder: Towards Foundation Models for Vehicle Routing Problemscited by 54
  5. 2022Learning to branch with Tree MDPscited by 45
  6. 2022A Survey for Solving Mixed Integer Programming via Machine Learningcited by 44
  7. 2022The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insightscited by 39
  8. 2023Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learningcited by 37
  9. 2024Towards Foundation Models for Mixed Integer Linear Programmingcited by 30
  10. 2024Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programmingcited by 24
  11. 2023A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availabilitycited by 21
  12. 2022Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective Trajectoriescited by 19
31 more
  1. 2024MILP-StuDio: MILP Instance Generation via Block Structure Decompositioncited by 17
  2. 2024Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP Methodscited by 15
  3. 2022An Improved Reinforcement Learning Algorithm for Learning to Branchcited by 14
  4. 2023Learning to Configure Separators in Branch-and-Cutcited by 14
  5. 2022Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branchcited by 12
  6. 2023Promoting Generalization for Exact Solvers via Adversarial Instance Augmentationcited by 12
  7. 2024Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programmingcited by 12
  8. 2024Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programmingcited by 8
  9. 2024Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusioncited by 8
  10. 2022DOGE-Train: Discrete Optimization on GPU with End-to-end Trainingcited by 6
  11. 2023Automatic MILP Solver Configuration By Learning Problem Similaritiescited by 5
  12. 2026LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programscited by 4
  13. 2023Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networkscited by 3
  14. 2025STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimizationcited by 3
  15. 2022Yordle: An Efficient Imitation Learning for Branch and Boundcited by 2
  16. 2025Are Your Generated Instances Truly Useful? GenBench-MILP: A Benchmark Suite for MILP Instance Generationcited by 2
  17. 2025Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimizationcited by 2
  18. 2023TreeDQN: Sample-Efficient Off-Policy Reinforcement Learning for Combinatorial Optimizationcited by 1
  19. 2024Network Interdiction Goes Neuralcited by 1
  20. 2025ReviBranch: Deep Reinforcement Learning for Branch-and-Bound with Revived Trajectoriescited by 1
  21. 2025Branching Strategies Based on Subgraph GNNs: A Study on Theoretical Promise versus Practical Realitycited by 1
  22. 2026A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attentioncited by 1
  23. 2022Travel the Same Path: A Novel TSP Solving Strategycited by 0
  24. 2023On Statistical Learning of Branch and Bound for Vehicle Routing Optimizationcited by 0
  25. 2024Learn2Aggregate: Supervised Generation of Chv'atal-Gomory Cuts Using Graph Neural Networkscited by 0
  26. 2025A Markov Decision Process for Variable Selection in Branch & Boundcited by 0
  27. 2026SRG: Score-based Relaxation-guided Generation for Mixed Integer Linear Programmingcited by 0
  28. 2026Speeding Up Mixed-Integer Programming Solvers with Sparse Learning for Branchingcited by 0
  29. 2026GraphBU: MILP Instance Generation with Graph-Native Block Unitscited by 0
  30. 2026A Weisfeiler-Leman Characterization of Global-Attention Graph Transformers for Mixed-Integer Linear Programscited by 0
  31. 2026Teaching LLMs to Generate Challenging MILP Instances via Solver Feedbackcited by 0