Characterization and recognition of partial 3-trees
SIAM Journal on Algebraic and Discrete Methods
Orienting graphs to optimize reachability
Information Processing Letters
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
Improved orientations of physical networks
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
Optimally orienting physical networks
RECOMB'11 Proceedings of the 15th Annual international conference on Research in computational molecular biology
Parameterized Complexity
Approximation algorithms for orienting mixed graphs
CPM'11 Proceedings of the 22nd annual conference on Combinatorial pattern matching
On making directed graphs transitive
Journal of Computer and System Sciences
Improved approximation for orienting mixed graphs
SIROCCO'12 Proceedings of the 19th international conference on Structural Information and Communication Complexity
Hi-index | 0.00 |
We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.