A Hybrid Encoding of Pseudo-Boolean Constraints into CNF

Aolong Zha, Miyuki Koshimura, Hiroshi Fujita

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 引用 (Scopus)

抜粋

Many NP-hard problems are commonly expressed with pseudo-Boolean (PB) constraints, which is a linear arithmetic constraint over Boolean variables. Conjunctive Normal Form (CNF) encoding always plays an important role in solving these constraints. In this paper, we propose Weighted Modulo Totalizer (WMTO) which is a hybrid CNF encoding of PB constraints between Modulo Totalizer (MTO) and Weighted Totalizer (WTO). WMTO uses less clauses and auxiliary variables than each of them. Our experimental results show that WMTO encodes the constraints compactly and the obtained clauses are efficiently handled by a state-of-the-art SAT solver.

元の言語英語
ホスト出版物のタイトルProceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ページ9-12
ページ数4
ISBN(電子版)9781538642030
DOI
出版物ステータス出版済み - 5 9 2018
イベント2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017 - Taipei, 台湾省、中華民国
継続期間: 12 1 201712 3 2017

出版物シリーズ

名前Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017

その他

その他2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017
台湾省、中華民国
Taipei
期間12/1/1712/3/17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Human-Computer Interaction

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  • これを引用

    Zha, A., Koshimura, M., & Fujita, H. (2018). A Hybrid Encoding of Pseudo-Boolean Constraints into CNF. : Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017 (pp. 9-12). (Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAAI.2017.15