A parameterized view on matroid optimization problems

Matroid theory gives us powerful techniques for understanding combinatorial optimization problems and for designing polynomial-time algorithms. However, several natural matroid problems, such as 3-matroid intersection, are NP-hard. Here we investigate these problems from the parameterized complexity...

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Bibliographic Details
Published in:Theoretical computer science Vol. 410; no. 44; pp. 4471 - 4479
Main Author: Marx, Dániel
Format: Journal Article Conference Proceeding
Language:English
Published: Oxford Elsevier B.V 17.10.2009
Elsevier
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ISSN:0304-3975, 1879-2294
Online Access:Get full text
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Summary:Matroid theory gives us powerful techniques for understanding combinatorial optimization problems and for designing polynomial-time algorithms. However, several natural matroid problems, such as 3-matroid intersection, are NP-hard. Here we investigate these problems from the parameterized complexity point of view: instead of the trivial n O ( k ) time brute force algorithm for finding a k -element solution, we try to give algorithms with uniformly polynomial (i.e., f ( k ) ⋅ n O ( 1 ) ) running time. The main result is that if the ground set of a represented linear matroid is partitioned into blocks of size ℓ , then we can determine in randomized time f ( k , ℓ ) ⋅ n O ( 1 ) whether there is an independent set that is the union of k blocks. As a consequence, algorithms with similar running time are obtained for other problems such as finding a k -element set in the intersection of ℓ matroids, or finding k terminals in a network such that each of them can be connected simultaneously to the source by ℓ disjoint paths.
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ISSN:0304-3975
1879-2294
DOI:10.1016/j.tcs.2009.07.027