Subexponential fixed-parameter algorithms for partial vector domination

Toshimasa Ishii, Hirotaka Ono, Yushi Uno

研究成果: 著書/レポートタイプへの貢献会議での発言

1 引用 (Scopus)

抄録

Given a graph G = (V, E) of order n and an n-dimensional non-negative vector d = (d(1), d(2),..., d(n)) called demand vector, the vector domination (resp., total vector domination) is the problem of finding a minimum S ⊆ V such that every vertex v in V \ S (resp., in V) has at least d(v) neighbors in S. The (total) vector domination is a generalization of many dominating set type problems, e.g., the dominating set problem, the k-tuple dominating set problem (this k is different from the solution size), and so on, and subexponential fixed-parameter algorithms with respect to solution size for apex-minor-free graphs (so for planar graphs) are known. In this paper, we consider maximization versions of the problems; that is, for a given integer k, the goal is to find an S ⊆ V with size k that maximizes the total sum of satisfied demands. For these problems, we design subexponential fixed-parameter algorithms with respect to k for apex-minor-free graphs.

元の言語英語
ホスト出版物のタイトルCombinatorial Optimization - Third International Symposium, ISCO 2014, Revised Selected Papers
出版者Springer Verlag
ページ292-304
ページ数13
ISBN(印刷物)9783319091730
DOI
出版物ステータス出版済み - 1 1 2014
イベント3rd International Symposium on Combinatorial Optimization, ISCO 2014 - Lisbon, ポルトガル
継続期間: 3 5 20143 7 2014

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8596 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

その他

その他3rd International Symposium on Combinatorial Optimization, ISCO 2014
ポルトガル
Lisbon
期間3/5/143/7/14

Fingerprint

Fixed-parameter Algorithms
Domination
Partial
Dominating Set
Apex
Minor
Graph in graph theory
Planar graph
n-dimensional
Maximise
Non-negative
Integer
Vertex of a graph

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Ishii, T., Ono, H., & Uno, Y. (2014). Subexponential fixed-parameter algorithms for partial vector domination. : Combinatorial Optimization - Third International Symposium, ISCO 2014, Revised Selected Papers (pp. 292-304). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 8596 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-09174-7_25

Subexponential fixed-parameter algorithms for partial vector domination. / Ishii, Toshimasa; Ono, Hirotaka; Uno, Yushi.

Combinatorial Optimization - Third International Symposium, ISCO 2014, Revised Selected Papers. Springer Verlag, 2014. p. 292-304 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 8596 LNCS).

研究成果: 著書/レポートタイプへの貢献会議での発言

Ishii, T, Ono, H & Uno, Y 2014, Subexponential fixed-parameter algorithms for partial vector domination. : Combinatorial Optimization - Third International Symposium, ISCO 2014, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻. 8596 LNCS, Springer Verlag, pp. 292-304, 3rd International Symposium on Combinatorial Optimization, ISCO 2014, Lisbon, ポルトガル, 3/5/14. https://doi.org/10.1007/978-3-319-09174-7_25
Ishii T, Ono H, Uno Y. Subexponential fixed-parameter algorithms for partial vector domination. : Combinatorial Optimization - Third International Symposium, ISCO 2014, Revised Selected Papers. Springer Verlag. 2014. p. 292-304. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-09174-7_25
Ishii, Toshimasa ; Ono, Hirotaka ; Uno, Yushi. / Subexponential fixed-parameter algorithms for partial vector domination. Combinatorial Optimization - Third International Symposium, ISCO 2014, Revised Selected Papers. Springer Verlag, 2014. pp. 292-304 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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