OMLT: optimization & machine learning toolkit
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
The optimization and machine learning toolkit (OMLT) is an open-source
software package incorporating neural network and gradient-boosted tree
surrogate models, which have been trained using machine learning, into larger
optimization problems. We discuss the advances in optimization technology that
made OMLT possible and show how OMLT seamlessly integrates with the algebraic
modeling language Pyomo. We demonstrate how to use OMLT for solving
decision-making problems in both computer science and engineering.
software package incorporating neural network and gradient-boosted tree
surrogate models, which have been trained using machine learning, into larger
optimization problems. We discuss the advances in optimization technology that
made OMLT possible and show how OMLT seamlessly integrates with the algebraic
modeling language Pyomo. We demonstrate how to use OMLT for solving
decision-making problems in both computer science and engineering.
Date Issued
2022
Date Acceptance
2022-11-01
Citation
Journal of Machine Learning Research, 2022, 23
ISSN
1532-4435
Publisher
Microtome Publishing
Journal / Book Title
Journal of Machine Learning Research
Volume
23
Copyright Statement
© 2022 Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D Laird, Ruth
Misener.
License: CC-BY 4.0, see https://creativecommons.org/licenses/by/4.0/. Attribution requirements are provided
at http://jmlr.org/papers/v23/22-0277.html.
Misener.
License: CC-BY 4.0, see https://creativecommons.org/licenses/by/4.0/. Attribution requirements are provided
at http://jmlr.org/papers/v23/22-0277.html.
License URL
Identifier
http://arxiv.org/abs/2202.02414v2
Subjects
cs.AI
cs.LG
math.OC
stat.ML
stat.ML
Notes
8 pages, 1 figure
Publication Status
Published
Article Number
349
Date Publish Online
2022-11