TY - GEN
T1 - Improved approximation for orienting mixed graphs
AU - Gamzu, Iftah
AU - Medina, Moti
PY - 2012
Y1 - 2012
N2 - An instance of the maximum mixed graph orientation problem consists of a mixed graph and a collection of source-target vertex pairs. The objective is to orient the undirected edges of the graph so as to maximize the number of pairs that admit a directed source-target path. This problem has recently arisen in the study of biological networks, and it also has applications in communication networks. In this paper, we identify an interesting local-to-global orientation property. This property enables us to modify the best known algorithms for maximum mixed graph orientation and some of its special structured instances, due to Elberfeld et al. (CPM '11), and obtain improved approximation ratios. We further proceed by developing an algorithm that achieves an even better approximation guarantee for the general setting of the problem. Finally, we study several well-motivated variants of this orientation problem.
AB - An instance of the maximum mixed graph orientation problem consists of a mixed graph and a collection of source-target vertex pairs. The objective is to orient the undirected edges of the graph so as to maximize the number of pairs that admit a directed source-target path. This problem has recently arisen in the study of biological networks, and it also has applications in communication networks. In this paper, we identify an interesting local-to-global orientation property. This property enables us to modify the best known algorithms for maximum mixed graph orientation and some of its special structured instances, due to Elberfeld et al. (CPM '11), and obtain improved approximation ratios. We further proceed by developing an algorithm that achieves an even better approximation guarantee for the general setting of the problem. Finally, we study several well-motivated variants of this orientation problem.
UR - http://www.scopus.com/inward/record.url?scp=84864070852&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-31104-8_21
DO - 10.1007/978-3-642-31104-8_21
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AN - SCOPUS:84864070852
SN - 9783642311031
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 253
BT - Structural Information and Communication Complexity - 19th International Colloquium, SIROCCO 2012, Proceedings
T2 - 19th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2012
Y2 - 30 June 2012 through 2 July 2012
ER -