TY - GEN
T1 - Approximation algorithms for B1-EPG graphs
AU - Epstein, Dror
AU - Golumbic, Martin Charles
AU - Morgenstern, Gila
PY - 2013
Y1 - 2013
N2 - The edge intersection graphs of paths on a grid (or EPG graphs) are graphs whose vertices can be represented as simple paths on a rectangular grid such that two vertices are adjacent if and only if the corresponding paths share at least one edge of the grid. We consider the case of single-bend paths, namely, the class known as B1-EPG graphs. The motivation for studying these graphs comes from the context of circuit layout problems. It is known that recognizing B1-EPG graphs is NP-complete, nevertheless, optimization problems when given a set of paths in the grid are of considerable practical interest. In this paper, we show that the coloring problem and the maximum independent set problem are both NP-complete for B1-EPG graphs, even when the EPG representation is given. We then provide efficient 4-approximation algorithms for both of these problems, assuming the EPG representation is given. We conclude by noting that the maximum clique problem can be optimally solved in polynomial time for B1-EPG graphs, even when the EPG representation is not given.
AB - The edge intersection graphs of paths on a grid (or EPG graphs) are graphs whose vertices can be represented as simple paths on a rectangular grid such that two vertices are adjacent if and only if the corresponding paths share at least one edge of the grid. We consider the case of single-bend paths, namely, the class known as B1-EPG graphs. The motivation for studying these graphs comes from the context of circuit layout problems. It is known that recognizing B1-EPG graphs is NP-complete, nevertheless, optimization problems when given a set of paths in the grid are of considerable practical interest. In this paper, we show that the coloring problem and the maximum independent set problem are both NP-complete for B1-EPG graphs, even when the EPG representation is given. We then provide efficient 4-approximation algorithms for both of these problems, assuming the EPG representation is given. We conclude by noting that the maximum clique problem can be optimally solved in polynomial time for B1-EPG graphs, even when the EPG representation is not given.
UR - http://www.scopus.com/inward/record.url?scp=84881189685&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40104-6_29
DO - 10.1007/978-3-642-40104-6_29
M3 - Conference contribution
AN - SCOPUS:84881189685
SN - 9783642401039
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 328
EP - 340
BT - Algorithms and Data Structures - 13th International Symposium, WADS 2013, Proceedings
T2 - 13th International Symposium on Algorithms and Data Structures, WADS 2013
Y2 - 12 August 2013 through 14 August 2013
ER -