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Bibliographic Details
Main Authors: Cardinal, Jean, Goaoc, Xavier, Wajsbrot, Sarah
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2504.16642
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author Cardinal, Jean
Goaoc, Xavier
Wajsbrot, Sarah
author_facet Cardinal, Jean
Goaoc, Xavier
Wajsbrot, Sarah
contents Geometric hitting set problems, in which we seek a smallest set of points that collectively hit a given set of ranges, are ubiquitous in computational geometry. Most often, the set is discrete and is given explicitly. We propose new variants of these problems, dealing with continuous families of convex polyhedra, and show that they capture decision versions of the two-level finite adaptability problem in robust optimization. We show that these problems can be solved in strongly polynomial time when the size of the hitting/covering set and the dimension of the polyhedra and the parameter space are constant. We also show that the hitting set problem can be solved in strongly quadratic time for one-parameter families of convex polyhedra in constant dimension. This leads to new tractability results for finite adaptability that are the first ones with so-called left-hand-side uncertainty, where the underlying problem is non-linear.
format Preprint
id arxiv_https___arxiv_org_abs_2504_16642
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hitting and Covering Affine Families of Convex Polyhedra, with Applications to Robust Optimization
Cardinal, Jean
Goaoc, Xavier
Wajsbrot, Sarah
Computational Geometry
Optimization and Control
Geometric hitting set problems, in which we seek a smallest set of points that collectively hit a given set of ranges, are ubiquitous in computational geometry. Most often, the set is discrete and is given explicitly. We propose new variants of these problems, dealing with continuous families of convex polyhedra, and show that they capture decision versions of the two-level finite adaptability problem in robust optimization. We show that these problems can be solved in strongly polynomial time when the size of the hitting/covering set and the dimension of the polyhedra and the parameter space are constant. We also show that the hitting set problem can be solved in strongly quadratic time for one-parameter families of convex polyhedra in constant dimension. This leads to new tractability results for finite adaptability that are the first ones with so-called left-hand-side uncertainty, where the underlying problem is non-linear.
title Hitting and Covering Affine Families of Convex Polyhedra, with Applications to Robust Optimization
topic Computational Geometry
Optimization and Control
url https://arxiv.org/abs/2504.16642