Faster Algorithms for Sparse ILP and Hypergraph Multi-Packing/Multi-Cover Problems

Fuente: arXiv
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Autori principali: Gribanov, Dmitry, Malyshev, Dmitry, Zolotykh, Nikolai
Natura: Preprint
Pubblicazione: 2022
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author Gribanov, Dmitry
Malyshev, Dmitry
Zolotykh, Nikolai
author_facet Gribanov, Dmitry
Malyshev, Dmitry
Zolotykh, Nikolai
contents In our paper, we consider the following general problems: check feasibility, count the number of feasible solutions, find an optimal solution, and count the number of optimal solutions in $P \cap Z^n$, assuming that $P$ is a polyhedron, defined by systems $A x \leq b$ or $Ax = b,\, x \geq 0$ with a sparse matrix $A$. We develop algorithms for these problems that outperform state of the art ILP and counting algorithms on sparse instances with bounded elements. We use known and new methods to develop new exponential algorithms for Edge/Vertex Multi-Packing/Multi-Cover Problems on graphs and hypergraphs. This framework consists of many different problems, such as the Stable Multi-set, Vertex Multi-cover, Dominating Multi-set, Set Multi-cover, Multi-set Multi-cover, and Hypergraph Multi-matching problems, which are natural generalizations of the standard Stable Set, Vertex Cover, Dominating Set, Set Cover, and Maximal Matching problems.
format Preprint
id arxiv_https___arxiv_org_abs_2201_08988
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Faster Algorithms for Sparse ILP and Hypergraph Multi-Packing/Multi-Cover Problems
Gribanov, Dmitry
Malyshev, Dmitry
Zolotykh, Nikolai
Computational Complexity
Data Structures and Algorithms
Combinatorics
In our paper, we consider the following general problems: check feasibility, count the number of feasible solutions, find an optimal solution, and count the number of optimal solutions in $P \cap Z^n$, assuming that $P$ is a polyhedron, defined by systems $A x \leq b$ or $Ax = b,\, x \geq 0$ with a sparse matrix $A$. We develop algorithms for these problems that outperform state of the art ILP and counting algorithms on sparse instances with bounded elements. We use known and new methods to develop new exponential algorithms for Edge/Vertex Multi-Packing/Multi-Cover Problems on graphs and hypergraphs. This framework consists of many different problems, such as the Stable Multi-set, Vertex Multi-cover, Dominating Multi-set, Set Multi-cover, Multi-set Multi-cover, and Hypergraph Multi-matching problems, which are natural generalizations of the standard Stable Set, Vertex Cover, Dominating Set, Set Cover, and Maximal Matching problems.
title Faster Algorithms for Sparse ILP and Hypergraph Multi-Packing/Multi-Cover Problems
topic Computational Complexity
Data Structures and Algorithms
Combinatorics
url https://arxiv.org/abs/2201.08988