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Threshold-based preprocessing for approximating the weighted dense k-subgraph problem

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  • Borgwardt, S.
  • Schmiedl, F.

Abstract

Based on an application in forestry, we study the dense k-subgraph problem: Given a parameter k∈N and an undirected weighted graph G, the task is to find a subgraph of G with k vertices such that the sum of the weights of the induced edges is maximized. The problem is well-known to be NP-hard and difficult to approximate if the underlying graph does not satisfy the triangle inequality.

Suggested Citation

  • Borgwardt, S. & Schmiedl, F., 2014. "Threshold-based preprocessing for approximating the weighted dense k-subgraph problem," European Journal of Operational Research, Elsevier, vol. 234(3), pages 631-640.
    • Handle: RePEc:eee:ejores:v:234:y:2014:i:3:p:631-640
    DOI: 10.1016/j.ejor.2013.09.027
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    References listed on IDEAS

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    1. Macambira, Elder Magalhaes & de Souza, Cid Carvalho, 2000. "The edge-weighted clique problem: Valid inequalities, facets and polyhedral computations," European Journal of Operational Research, Elsevier, vol. 123(2), pages 346-371, June.
    2. Hunting, Marcel & Faigle, Ulrich & Kern, Walter, 2001. "A Lagrangian relaxation approach to the edge-weighted clique problem," European Journal of Operational Research, Elsevier, vol. 131(1), pages 119-131, May.
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