End-to-End Constrained Optimization Learning: A Survey

Kotary, James; Fioretto, Ferdinando; Van Hentenryck, Pascal; Wilder, Bryan

doi:10.24963/ijcai.2021/610

End-to-End Constrained Optimization Learning: A Survey

James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4475-4482.

https://doi.org/10.24963/ijcai.2021/610

Keywords

Machine learning: General
Constraints and SAT: General

Abstract

This paper surveys the recent attempts at leveraging machine learning to solve constrained optimization problems. It focuses on surveying the work on integrating combinatorial solvers and optimization methods with machine learning architectures.

These approaches hold the promise to develop new hybrid machine learning and optimization methods to predict fast, approximate, solutions to combinatorial problems and to enable structural logical inference. This paper presents a conceptual review of the recent advancements in this emerging area.

James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, and Bryan Wilder. 2021. End-to-End Constrained Optimization Learning: A Survey. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 4475–4482. https://doi.org/10.24963/ijcai.2021/610

@inproceedings{ijcai2021p610,
  title     = {End-to-End Constrained Optimization Learning: A Survey},
  author    = {Kotary, James and Fioretto, Ferdinando and Van Hentenryck, Pascal and Wilder, Bryan},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {4475--4482},
  year      = {2021},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2021/610},
  url       = {https://doi.org/10.24963/ijcai.2021/610},
}

TY  - CPAPER
TI  - End-to-End Constrained Optimization Learning: A Survey
AU  - Kotary, James
AU  - Fioretto, Ferdinando
AU  - Van Hentenryck, Pascal
AU  - Wilder, Bryan
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 4475
EP  - 4482
DO  - 10.24963/ijcai.2021/610
UR  - https://doi.org/10.24963/ijcai.2021/610
ER  -