A New Solver for the Minimum Weighted Vertex Cover Problem

  • Hong XuEmail author
  • T. K. Satish Kumar
  • Sven Koenig
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9676)


Given a vertex-weighted graph \(G = \langle V, E \rangle \), the minimum weighted vertex cover (MWVC) problem is to choose a subset of vertices with minimum total weight such that every edge in the graph has at least one of its endpoints chosen. While there are good solvers for the unweighted version of this NP-hard problem, the weighted version—i.e., the MWVC problem—remains understudied despite its common occurrence in many areas of AI—like combinatorial auctions, weighted constraint satisfaction, and probabilistic reasoning. In this paper, we present a new solver for the MWVC problem based on a novel reformulation to a series of SAT instances using a primal-dual approximation algorithm as a starting point. We show that our SAT-based MWVC solver (SBMS) significantly outperforms other methods.



The research at USC was supported by NSF under grant numbers 1409987 and 1319966 and a MURI under grant number N00014-09-1-1031. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the sponsoring organizations, agencies or the U.S. government.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of Southern CaliforniaLos AngelesUSA

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