Multi-parameter Analysis for Local Graph Partitioning Problems: Using Greediness for Parameterization - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Algorithmica Année : 2015

Multi-parameter Analysis for Local Graph Partitioning Problems: Using Greediness for Parameterization

Résumé

We study the parameterized complexity of a broad class of problems called “local graph partitioning problems” that includes the classical fixed cardinality problems as max k-vertex cover, k-densest subgraph, etc. By developing a technique that we call “greediness-for-parameterization”, we obtain fixed parameter algorithms with respect to a pair of parameters k, the size of the solution (but not its value) and Δ, the maximum degree of the input graph. In particular, greediness-for-parameterization improves asymptotic running times for these problems upon random separation (that is a special case of color coding) and is more intuitive and simple. Then, we show how these results can be easily extended for getting standard-parameterization results (i.e., with parameter the value of the optimal solution) for a well known local graph partitioning problem.

Dates et versions

hal-01200582 , version 1 (16-09-2015)

Identifiants

Citer

Edouard Bonnet, Bruno Escoffier, Vangelis Paschos, Emeric Tourniaire. Multi-parameter Analysis for Local Graph Partitioning Problems: Using Greediness for Parameterization. Algorithmica, 2015, 71 (3), pp.566-580. ⟨10.1007/s00453-014-9920-6⟩. ⟨hal-01200582⟩
96 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More