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CCEHC: An efficient local search algorithm forweighted partial maximum satisfiability

  • Chuan Luo
  • , Shaowei Cai
  • , Kaile Su
  • , Wenxuan Huang
  • Chinese Academy of Sciences
  • University of Jinan
  • Massachusetts Institute of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Weighted partial maximum satisfiability (WPMS) is a significant generalization of maximum satisfiability (MAX-SAT), with many important applications. Recently, breakthroughs have been made on stochastic local search (SLS) for weighted MAXSAT and (unweighted) partial MAX-SAT (PMS). However, the performance of SLS for WPMS lags far behind. In this work, we present a new SLS algorithm named CCEHC for WPMS. CCEHC is mainly based on a heuristic emphasizing hard clauses, which has three components: a variable selection mechanism focusing on configuration checking based only on hard clauses, a weighting scheme for hard clauses, and a biased random walk component. Experiments show that CCEHC significantly outperforms its state-of-the-art SLS competitors. Experiments comparing CCEHC with a state-of-the-art complete solver indicate the effectiveness of CCEHC on a number of application WPMS instances.

源语言英语
主期刊名26th International Joint Conference on Artificial Intelligence, IJCAI 2017
编辑Carles Sierra
出版商International Joint Conferences on Artificial Intelligence
5030-5034
页数5
ISBN(电子版)9780999241103
出版状态已出版 - 2017
已对外发布
活动26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, 澳大利亚
期限: 19 8月 201725 8月 2017

出版系列

姓名IJCAI International Joint Conference on Artificial Intelligence
ISSN(印刷版)1045-0823

会议

会议26th International Joint Conference on Artificial Intelligence, IJCAI 2017
国家/地区澳大利亚
Melbourne
时期19/08/1725/08/17

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