Component Order Connectivity in Directed Graphs

Author:

Bang-Jensen Jørgen,Eiben Eduard,Gutin GregoryORCID,Wahlström Magnus,Yeo Anders

Abstract

AbstractA directed graph D is semicomplete if for every pair xy of vertices of D,  there is at least one arc between x and y. Thus, a tournament is a semicomplete digraph. In the Directed Component Order Connectivity (DCOC) problem, given a digraph $$D=(V,A)$$ D = ( V , A ) and a pair of natural numbers k and $$\ell $$ , we are to decide whether there is a subset X of V of size k such that the largest strongly connected component in $$D-X$$ D - X has at most $$\ell $$ vertices. Note that DCOC reduces to the Directed Feedback Vertex Set problem for $$\ell =1.$$ = 1 . We study the parameterized complexity of DCOC for general and semicomplete digraphs with the following parameters: $$k, \ell ,\ell +k$$ k , , + k and $$n-\ell $$ n - . In particular, we prove that DCOC with parameter k on semicomplete digraphs can be solved in time $$O^*(2^{16k})$$ O ( 2 16 k ) but not in time $$O^*(2^{o(k)})$$ O ( 2 o ( k ) ) unless the Exponential Time Hypothesis (ETH) fails. The upper bound $$O^*(2^{16k})$$ O ( 2 16 k ) implies the upper bound $$O^*(2^{16(n-\ell )})$$ O ( 2 16 ( n - ) ) for the parameter $$n-\ell .$$ n - . We complement the latter by showing that there is no algorithm of time complexity $$O^*(2^{o({n-\ell })})$$ O ( 2 o ( n - ) ) unless ETH fails. Finally, we improve (in dependency on $$\ell $$ ) the upper bound of Göke, Marx and Mnich (2019) for the time complexity of DCOC with parameter $$\ell +k$$ + k on general digraphs from $$O^*(2^{O(k\ell \log (k\ell ))})$$ O ( 2 O ( k log ( k ) ) ) to $$O^*(2^{O(k\log (k\ell ))}).$$ O ( 2 O ( k log ( k ) ) ) . Note that Drange, Dregi and van ’t Hof (2016) proved that even for the undirected version of DCOC on split graphs there is no algorithm of running time $$O^*(2^{o(k\log \ell )})$$ O ( 2 o ( k log ) ) unless ETH fails and it is a long-standing problem to decide whether Directed Feedback Vertex Set admits an algorithm of time complexity $$O^*(2^{o(k\log k)}).$$ O ( 2 o ( k log k ) ) .

Funder

Danmarks Frie Forskningsfond

Leverhulme Trust

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,General Computer Science

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