Faster Algorithms for Sparse ILP and Hypergraph Multi-Packing/Multi-Cover Problems
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| _version_ | 1866916098477129728 |
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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 |