An Effective Branching Strategy for Some Parameterized Edge Modification Problems with Multiple Forbidden Induced Subgraphs

  • Yunlong Liu
  • Jianxin Wang
  • Chao Xu
  • Jiong Guo
  • Jianer Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7936)


Branching on forbidden induced subgraphs is a genetic strategy to obtain parameterized algorithms for many edge modification problems. For such a problem in which the graph property is defined by multiple forbidden induced subgraphs, branching process is trivially performed on each subgraph. Thus, the size of the resulting search tree is dominated by the size of the largest forbidden subgraph. In this paper, we present a simple strategy for deriving significantly improved branching rules for dealing with multiple forbidden subgraphs by edge modifications. The basic idea hereby is that while constructing branching rules for the largest forbidden subgraph, we sufficiently take into account the structural relationship between it and other forbidden subgraphs. By applying this strategy, we obtain improved parameterized algorithms for edge modification problems for several graph properties such as proper interval, 3-leaf power, threshold and co-trivially perfect graphs.


Search Tree Polynomial Kernel Graph Property Graph Class Perfect Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yunlong Liu
    • 1
    • 2
  • Jianxin Wang
    • 1
  • Chao Xu
    • 1
  • Jiong Guo
    • 3
  • Jianer Chen
    • 1
    • 4
  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaP.R. China
  2. 2.College of Mathematics and Computer Science, Key Laboratory of High Performance Computing and Stochastic Information Processing(Ministry of Education of China)Hunan Normal UniversityChangshaP.R. China
  3. 3.Universität des SaarlandesSaarbrückenGermany
  4. 4.Department of Computer Science and EngineeringTexas A&M UniversityCollege StationUSA

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