Multi-parameter Complexity Analysis for Constrained Size Graph Problems: Using Greediness for Parameterization
نویسندگان
چکیده
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 " 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 ∆, 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.
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