The Machine Learning for Combinatorial Optimization Competition (ML4CO):\n Results and Insights Article Swipe
Maxime Gasse
,
Quentin Cappart
,
Jonas Charfreitag
,
Laurent Charlin
,
Didier Chételat
,
Antonia Chmiela
,
Justin Dumouchelle
,
Ambros Gleixner
,
Aleksandr M. Kazachkov
,
Elias L. Khalil
,
Paweł Lichocki
,
Andrea Lodi
,
Miles Lubin
,
Chris J. Maddison
,
Christopher G. Morris
,
Dimitri J. Papageorgiou
,
Augustin Parjadis
,
Sebastian Pokutta
,
Antoine Prouvost
,
Lara Scavuzzo
,
Giulia Zarpellon
,
Linxin Yang
,
Sha Lai
,
Akang Wang
,
Xiaodong Luo
,
Xiang Zhou
,
Haohan Huang
,
Shengcheng Shao
,
Yuanming Zhu
,
Dong Zhang
,
Quan Tao
,
Zixuan Cao
,
Yang Xu
,
Zhewei Huang
,
Shuchang Zhou
,
Chen Bin-bin
,
He Minggui
,
Hao Hao
,
Zhi‐yu Zhang
,
An Zhiwu
,
Kun Mao
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2203.02433
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2203.02433
Combinatorial optimization is a well-established area in operations research\nand computer science. Until recently, its methods have focused on solving\nproblem instances in isolation, ignoring that they often stem from related data\ndistributions in practice. However, recent years have seen a surge of interest\nin using machine learning as a new approach for solving combinatorial problems,\neither directly as solvers or by enhancing exact solvers. Based on this\ncontext, the ML4CO aims at improving state-of-the-art combinatorial\noptimization solvers by replacing key heuristic components. The competition\nfeatured three challenging tasks: finding the best feasible solution, producing\nthe tightest optimality certificate, and giving an appropriate solver\nconfiguration. Three realistic datasets were considered: balanced item\nplacement, workload apportionment, and maritime inventory routing. This last\ndataset was kept anonymous for the contestants.\n
Related Topics
Concepts
Computer science
Context (archaeology)
Heuristic
Solver
Combinatorial optimization
Bayesian optimization
Mathematical optimization
Workload
Competition (biology)
Artificial intelligence
Machine learning
Theoretical computer science
Mathematics
Algorithm
Programming language
Biology
Paleontology
Ecology
Operating system
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2203.02433
- https://arxiv.org/pdf/2203.02433
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4225781402
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4225781402Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2203.02433Digital Object Identifier
- Title
-
The Machine Learning for Combinatorial Optimization Competition (ML4CO):\n Results and InsightsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-04Full publication date if available
- Authors
-
Maxime Gasse, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros Gleixner, Aleksandr M. Kazachkov, Elias L. Khalil, Paweł Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher G. Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Shengcheng Shao, Yuanming Zhu, Dong Zhang, Quan Tao, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Chen Bin-bin, He Minggui, Hao Hao, Zhi‐yu Zhang, An Zhiwu, Kun MaoList of authors in order
- Landing page
-
https://arxiv.org/abs/2203.02433Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2203.02433Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2203.02433Direct OA link when available
- Concepts
-
Computer science, Context (archaeology), Heuristic, Solver, Combinatorial optimization, Bayesian optimization, Mathematical optimization, Workload, Competition (biology), Artificial intelligence, Machine learning, Theoretical computer science, Mathematics, Algorithm, Programming language, Biology, Paleontology, Ecology, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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