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A Computational Approach to Study Ramsey Numbers

Research Project

Project/Area Number 17K00307
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Intelligent informatics
Research InstitutionKyushu University

Principal Investigator

Fujita Hiroshi  九州大学, システム情報科学研究院, 准教授 (70284552)

Co-Investigator(Kenkyū-buntansha) 越村 三幸  九州大学, システム情報科学研究院, 助教 (30274492)
Project Period (FY) 2017-04-01 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
KeywordsRamsey number / SAT solver / Ramseyグラフ / 局所探索 / 深層学習 / Python / Ramsey数 / SATソルバー / MaxSATソルバー / 基数制約
Outline of Final Research Achievements

We have succeeded in finding some rare Ramsey graphs whose adjacency matrices are persymmetric, that are essential for the study of Ramsey numbers whose determination is one of the most famous and difficult problems in discrete mathematics.
For this research, it is indispensable to use various methods and problem solvers in computer science. We have developed high performance SAT solvers and MaxSAT solvers, achieving high rankings in some major international competitions. We have also developed local search based solvers specifically designed to search Ramsey graphs, whose performance exceeded the limit of more general purpose solvers.
We have also made a beginning of applying deep learning to discrete mathematics problems like search for Ramsey graphs.

Academic Significance and Societal Importance of the Research Achievements

数学の数ある未解決問題の中でも、その解決に向けて計算科学的手段が本質的な役割を果たす場合が少なくない。その一例としてのRamsey数確定に関する問題において、SATソルバー等を利用した計算科学的アプローチが実際に奏功することが確認された。
本研究の主要な成果である高性能なSATソルバーやMaxSATソルバー、およびそれらを利用した問題解決手法は、数学に限らず様々な分野で活用され、多くの実践的な問題解決における貢献が期待される。

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (7 results)

All 2020 2019 2017

All Journal Article (4 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 4 results,  Open Access: 1 results) Presentation (3 results)

  • [Journal Article] N-level Modulo-Based CNF encodings of Pseudo-Boolean constraints for MaxSAT2019

    • Author(s)
      Aolong Zha, Miyuki Koshimura, Hiroshi Fujita
    • Journal Title

      Constraints

      Volume: 24 Issue: 2 Pages: 133-161

    • DOI

      10.1007/s10601-018-9299-0

    • Related Report
      2019 Annual Research Report 2018 Research-status Report
    • Peer Reviewed
  • [Journal Article] A comparative analysis and improvement of MaxSAT encodings for coalition structure generation under MC-nets2019

    • Author(s)
      Xiaojuan Liao、Miyuki Koshimura
    • Journal Title

      Journal of Logic and Computation

      Volume: 29 Issue: 6 Pages: 913-931

    • DOI

      10.1093/logcom/exz017

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Improved WPM Encoding for Coalition Structure Generation under MC-nets2019

    • Author(s)
      Xiaojuan Liao, Miyuki Koshimura, Kazuki Nomoto, Suguru Ueda, Yuko Sakurai, Makoto Yokoo
    • Journal Title

      Constraints

      Volume: 24 Pages: 25-55

    • Related Report
      2018 Research-status Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Mixed Radix Weight Totalizer Encoding for Pseudo-Boolean Constraints2017

    • Author(s)
      Aolong Zha, Naoki Uemura, Miyuki Koshimura, and Hiroshi Fujita
    • Journal Title

      Proceedings of 29th International Conference on Tools with Artificial Intelligence

      Volume: 1 Pages: 868-875

    • DOI

      10.1109/ictai.2017.00135

    • Related Report
      2017 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] 細胞数カウントに向けたCNNを用いた尿中有形成分の分類2020

    • Author(s)
      淺倉 健太、越村 三幸、池田 大輔、藤田 博
    • Organizer
      火の国情報シンポジウム2020
    • Related Report
      2019 Annual Research Report
  • [Presentation] Coalition Structure Generation for Partition Function Games Utilizing a Concise Graphical Representation2019

    • Author(s)
      Miyuki Koshimura, Aolong Zha, Kazuki Nomoto, Suguru Ueda, Yuko Sakurai, Makoto Yokoo
    • Organizer
      The 4th Kakenhi Kiban-A&B/NII Collaborate Research Meeting
    • Related Report
      2018 Research-status Report
  • [Presentation] 混合基数を用いた擬似ブール制約のSAT符号化2017

    • Author(s)
      上村 直輝,藤田 博,越村 三幸,査 澳龍
    • Organizer
      人工知能学会 第103回人工知能基本問題研究会(SIG-FPAI)
    • Related Report
      2017 Research-status Report

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Published: 2017-04-28   Modified: 2021-02-19  

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