Extracting Alternative Solutions from Benders Decomposition

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Bibliographische Detailangaben
Hauptverfasser:	Viens, Matthew, Hart, William E., Ferris, Michael
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Optimization and Control
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

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author	Viens, Matthew Hart, William E. Ferris, Michael
author_facet	Viens, Matthew Hart, William E. Ferris, Michael
contents	We show how to extract alternative solutions for optimization problems solved by Benders Decomposition. In practice, alternative solutions provide useful insights for complex applications; some solvers do support generation of alternative solutions but none appear to support such generation when using Benders Decomposition. We propose a new post-processing method that extracts multiple optimal and near-optimal solutions using the cut-pool generated during Benders Decomposition. Further, we provide a geometric framework for understanding how the adaptive approximation in Benders Decomposition relates to alternative solutions. We demonstrate this technique on stochastic programming and interdiction modeling, and we highlight use cases that require the ability to enumerate all optimal solutions.
format	Preprint
id	arxiv_https___arxiv_org_abs_2509_08671
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Extracting Alternative Solutions from Benders Decomposition Viens, Matthew Hart, William E. Ferris, Michael Optimization and Control We show how to extract alternative solutions for optimization problems solved by Benders Decomposition. In practice, alternative solutions provide useful insights for complex applications; some solvers do support generation of alternative solutions but none appear to support such generation when using Benders Decomposition. We propose a new post-processing method that extracts multiple optimal and near-optimal solutions using the cut-pool generated during Benders Decomposition. Further, we provide a geometric framework for understanding how the adaptive approximation in Benders Decomposition relates to alternative solutions. We demonstrate this technique on stochastic programming and interdiction modeling, and we highlight use cases that require the ability to enumerate all optimal solutions.
title	Extracting Alternative Solutions from Benders Decomposition
topic	Optimization and Control
url	https://arxiv.org/abs/2509.08671

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