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LS-DTKMS: A Local Search Algorithm for Diversified Top-k MaxSAT Problem

Authors Junping Zhou , Jiaxin Liang , Minghao Yin , Bo He

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Author Details

Junping Zhou
  • School of Information Science and Technology, Northeast Normal University, Changchun, China
Jiaxin Liang
  • School of Information Science and Technology, Northeast Normal University, Changchun, China
Minghao Yin
  • School of Information Science and Technology, Northeast Normal University, Changchun, China
  • Key Laboratory of Applied Statistics of MOE, Northeast Normal University, Changchun, China
Bo He
  • School of Information Science and Technology, Northeast Normal University, Changchun, China

Funding

This work is supported by Science and Technology Development Program of Jilin Province (20230101060JC and YDZJ202201ZYTS412), NSFC (under Grant No.61976050, 61972384), the Fundamental Research Funds for the Central Universities 2412019ZD013, and Jilin Science and Technology Department 20200201280JC.

Acknowledgements

We would like to thank all the anonymous reviewers for their helpful comments.

Cite AsGet BibTex

Junping Zhou, Jiaxin Liang, Minghao Yin, and Bo He. LS-DTKMS: A Local Search Algorithm for Diversified Top-k MaxSAT Problem. In 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 271, pp. 29:1-29:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.SAT.2023.29

Abstract

The Maximum Satisfiability (MaxSAT), an important optimization problem, has a range of applications, including network routing, planning and scheduling, and combinatorial auctions. Among these applications, one usually benefits from having not just one single solution, but k diverse solutions. Motivated by this, we study an extension of MaxSAT, named Diversified Top-k MaxSAT (DTKMS) problem, which is to find k feasible assignments of a given formula such that each assignment satisfies all hard clauses and all of them together satisfy the maximum number of soft clauses. This paper presents a local search algorithm, LS-DTKMS, for DTKMS problem, which exploits novel scoring functions to select variables and assignments. Experiments demonstrate that LS-DTKMS outperforms the top-k MaxSAT based DTKMS solvers and state-of-the-art solvers for diversified top-k clique problem.

Subject Classification

ACM Subject Classification
  • Theory of computation → Random search heuristics
  • Theory of computation → Constraint and logic programming
Keywords
  • Top-k
  • MaxSAT
  • local search

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Supplementary Materials

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