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Bibliographic Details
Main Authors: Hojny, Christopher, Liberti, Leo
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.02305
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author Hojny, Christopher
Liberti, Leo
author_facet Hojny, Christopher
Liberti, Leo
contents Minimum distance constraints (minDCs) appear in many geometric optimization problems. They pose major challenges for mixed-integer nonlinear programming (MINLP) due to their reverse-convexity. We develop new algorithms for tightening variable bounds in general MINLPs with minDCs. Because many such problems exhibit substantial symmetry, we further introduce a practical approach for handling rotation symmetries via separation of lexicographic constraints induced by Givens rotations. In a computational study, we examine the performance of the various methods and determine the scenarios in which each approach demonstrates superiority.
format Preprint
id arxiv_https___arxiv_org_abs_2605_02305
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A computational comparison of handling distance constraints in MINLP
Hojny, Christopher
Liberti, Leo
Optimization and Control
Minimum distance constraints (minDCs) appear in many geometric optimization problems. They pose major challenges for mixed-integer nonlinear programming (MINLP) due to their reverse-convexity. We develop new algorithms for tightening variable bounds in general MINLPs with minDCs. Because many such problems exhibit substantial symmetry, we further introduce a practical approach for handling rotation symmetries via separation of lexicographic constraints induced by Givens rotations. In a computational study, we examine the performance of the various methods and determine the scenarios in which each approach demonstrates superiority.
title A computational comparison of handling distance constraints in MINLP
topic Optimization and Control
url https://arxiv.org/abs/2605.02305