Learning to reoptimize: a GNN-aided fix-and-optimize approac…
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- DOI 10.48550/arxiv.2605.27339
- OpenAlex ID W7162503419
- Type Preprint
- Language EN
- Published 26 May 2026
- Source arXiv (Cornell University)
- Publisher Cornell University
- Countries 2
- Institutions 3
- Added 28 May 2026
- Updated 28 Oct 2026
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Learning to reoptimize: a GNN-aided fix-and-optimize approach and an application to the Lot Sizing problem
Preprint 2026 EN Green
In many operational contexts, solutions to NP-hard combinatorial optimization problems, modeled by means of Mixed-Integer Linear Programming (MILP), may become infeasible due to unpredictable disruptions. Typically, reoptimizing by solving the MILP formulation on the perturbed instance is not possible as new solutions must be obtained in a very short computing time, while simple repairing heuristi…
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5 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Mathieu Lerouge | Laboratori Guglielmo Marconi (… (IT) | |
| 2 | Andrea Lodi | Cornell University (US) Laboratori Guglielmo Marconi (… (IT) +1 | |
| 3 | Enrico Malaguti | Laboratori Guglielmo Marconi (… (IT) | |
| 4 | Michele Monaci | Laboratori Guglielmo Marconi (… (IT) | |
| 5 | Filippo Focacci | — | — |
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