Greedy Localization and Color-Coding: Improved Matching and Packing Algorithms

  • Yang Liu
  • Songjian Lu
  • Jianer Chen
  • Sing-Hoi Sze
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4169)


Matching and packing problems have formed an important class of NP-hard problems. There have been a number of recently developed techniques for parameterized algorithms for these problems, including greedy localization, color-coding plus dynamic programming, and randomized divide-and-conquer. In this paper, we provide further theoretical study on the structures of these problems, and develop improved algorithmic methods that combine existing and new techniques to obtain improved algorithms for matching and packing problems. For the 3-set packing problem, we present a deterministic algorithm of time O *(4.613k), which significantly improves the previous best deterministic algorithm of time O *(12.83k). For the 3-d matching problem, we develop a new randomized algorithm of running time O *(2.323k) and a new deterministic algorithm of running time O *(2.773k). Our randomized algorithm improves the previous best randomized algorithm of running time O *(2.523k), and our deterministic algorithm significantly improves the previous best deterministic algorithm of running time O *(12.83k). Our results also imply improved algorithms for various triangle packing problems in graphs.


Time Complexity Dynamic Programming Match Problem Packing Problem Dynamic Programming Algorithm 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yang Liu
    • 1
  • Songjian Lu
    • 1
  • Jianer Chen
    • 1
  • Sing-Hoi Sze
    • 1
    • 2
  1. 1.Department of Computer Science 
  2. 2.Department of Biochemistry & BiophysicsTexas A&M UniversityCollege StationUSA

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