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Computing densest k-subgraph with structural parameters

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  • Tesshu Hanaka

    (Kyushu University)

Abstract

Densest k-Subgraph is the problem to find a vertex subset S of size k such that the number of edges in the subgraph induced by S is maximized. In this paper, we show that Densest k-Subgraph is fixed parameter tractable when parameterized by neighborhood diversity, block deletion number, distance-hereditary deletion number, and cograph deletion number, respectively. Furthermore, we give a 2-approximation $$2^{{{\texttt{tc}}(G)}/2}n^{O(1)}$$ 2 tc ( G ) / 2 n O ( 1 ) -time algorithm where $${{\texttt{tc}}(G)}$$ tc ( G ) is the twin cover number of an input graph G.

Suggested Citation

  • Tesshu Hanaka, 2023. "Computing densest k-subgraph with structural parameters," Journal of Combinatorial Optimization, Springer, vol. 45(1), pages 1-17, January.
    • Handle: RePEc:spr:jcomop:v:45:y:2023:i:1:d:10.1007_s10878-022-00927-1
    DOI: 10.1007/s10878-022-00927-1
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    References listed on IDEAS

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    1. Bourgeois, Nicolas & Giannakos, Aristotelis & Lucarelli, Giorgio & Milis, Ioannis & Paschos, Vangelis Th., 2017. "Exact and superpolynomial approximation algorithms for the densest k-subgraph problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 894-903.
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    Cited by:

    1. Zhongling Liu & Wenbin Chen & Fufang Li & Ke Qi & Jianxiong Wang, 2024. "Algorithms for Densest Subgraphs of Vertex-Weighted Graphs," Mathematics, MDPI, vol. 12(14), pages 1-9, July.

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