Iterative Expansion and Color Coding: An Improved Algorithm for 3D-Matching

Authors:
Jianer Chen;Yang Liu;Songjian Lu;Sing-Hoi Sze;Fenghui Zhang
Affiliations:
Texas A&M University;University of Texas - Pan American;Medical University of South Carolina;Texas A&M University;Google Inc.
Venue:
ACM Transactions on Algorithms (TALG)
Year:
2012

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Abstract

The research in the parameterized 3d-matching problem has yielded a number of new algorithmic techniques and an impressive list of improved algorithms. In this article, a new deterministic algorithm for the problem is developed that integrates and improves a number of known techniques, including greedy localization, dynamic programming, and color coding. The new algorithm, which either constructs a matching of k triples in a given triple set or correctly reports that no such a matching exists, runs in time O*(2.803k), improving a long list of previous algorithms for the problem.