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Approximation Strategies for Incomplete MaxSAT

  • Saurabh Joshi
  • Prateek Kumar
  • Ruben Martins
  • Sukrut Rao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11008)

Abstract

Incomplete MaxSAT solving aims to quickly find a solution that attempts to minimize the sum of the weights of the unsatisfied soft clauses without providing any optimality guarantees. In this paper, we propose two approximation strategies for improving incomplete MaxSAT solving. In one of the strategies, we cluster the weights and approximate them with a representative weight. In another strategy, we break up the problem of minimizing the sum of weights of unsatisfiable clauses into multiple minimization subproblems. Experimental results show that approximation strategies can be used to find better solutions than the best incomplete solvers in the MaxSAT Evaluation 2017.

Keywords

MaxSAT Incomplete Approximation 

Notes

Acknowledgements

This work is partially funded by ECR 2017 grant from SERB, DST, India, NSF award #1762363 and CMU/AIR/0022/2017 grant. Authors would like to thank the anonymous reviewers for their helpful comments, and Saketha Nath for lending his servers for the experiments.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Saurabh Joshi
    • 1
  • Prateek Kumar
    • 1
  • Ruben Martins
    • 2
  • Sukrut Rao
    • 1
  1. 1.Indian Institute of Technology HyderabadSangareddyIndia
  2. 2.Carnegie Mellon UniversityPittsburghUSA

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