dc.contributor.author | Lin, Jinkun | |
dc.contributor.author | Cai, Shaowei | |
dc.contributor.author | Luo, Chuan | |
dc.contributor.author | Su, Kaile | |
dc.contributor.editor | Carles Sierra | |
dc.date.accessioned | 2017-12-05T01:18:41Z | |
dc.date.available | 2017-12-05T01:18:41Z | |
dc.date.issued | 2017 | |
dc.identifier.doi | 10.24963/ijcai.2017/73 | |
dc.identifier.uri | http://hdl.handle.net/10072/355067 | |
dc.description.abstract | The graph coloring problem (GCP) is one of the most studied NP hard problems and has numerous applications. Despite the practical importance of GCP, there are limited works in solving GCP for very large graphs. This paper explores techniques for solving GCP on very large real world graphs.We first propose a reduction rule for GCP, which is based on a novel concept called degree bounded independent set.The rule is iteratively executed by interleaving between lower bound computation and graph reduction. Based on this rule, we develop a novel method called FastColor, which also exploits fast clique and coloring heuristics. We carry out experiments to compare our method FastColor with two best algorithms for coloring large graphs we could find. Experiments on a broad range of real world large graphs show the superiority of our method. Additionally, our method maintains both upper bound and lower bound on the optimal solution, and thus it proves an optimal solution when the upper bound meets the lower bound. In our experiments, it proves the optimal solution for 97 out of 142 instances. | |
dc.description.peerreviewed | Yes | |
dc.language | English | |
dc.publisher | International Joint Conferences on Artifical Intelligence (IJCAI) | |
dc.publisher.place | United States | |
dc.relation.ispartofconferencename | IJCAI-17 | |
dc.relation.ispartofconferencetitle | Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) | |
dc.relation.ispartofdatefrom | 2017-08-19 | |
dc.relation.ispartofdateto | 2017-08-25 | |
dc.relation.ispartoflocation | Melbourne, Vic, Australia | |
dc.subject.fieldofresearch | Artificial intelligence not elsewhere classified | |
dc.subject.fieldofresearchcode | 460299 | |
dc.title | A reduction based method for coloring very large graphs | |
dc.type | Conference output | |
dc.type.description | E1 - Conferences | |
dc.type.code | E - Conference Publications | |
dc.description.version | Version of Record (VoR) | |
gro.rights.copyright | © 2017 International Joint Conference on Artificial Intelligence. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version. | |
gro.hasfulltext | Full Text | |
gro.griffith.author | Su, Kaile | |