A Possibilistic and Stochastic Programming Approach to Fuzzy Random MST Problems(Neural Networks and Fuzzy Systems, <Special Section>Recent Advances in Circuits and Systems)

• KATAGIRI Hideki

  Graduate School of Engineering, Hiroshima University

• MERMRI El Bekkaye

  Graduate School of Engineering, Hiroshima University

• SAKAWA Masatoshi

  Graduate School of Engineering, Hiroshima University

• KATO Kosuke

  Graduate School of Engineering, Hiroshima University

• NISHIZAKI Ichiro

  Graduate School of Engineering, Hiroshima University

抄録

This paper deals with minimum spanning tree problems where each edge weight is a fuzzy random variable. In order to consider the imprecise nature of the decision maker's judgment, a fuzzy goal for the objective function is introduced. A novel decision making model is constructed based on possibility theory and on a stochastic programming model. It is shown that the problem including both randomness and fuzziness is reduced to a deterministic equivalent problem. Finally, a polynomial-time algorithm is provided to solve the problem.

収録刊行物

• IEICE transactions on information and systems

  IEICE transactions on information and systems 88 (8), 1912-1919, 2005-08-01

  一般社団法人電子情報通信学会

キーワード

• fuzzy random variable
• minimum spanning tree problem
• possibility theory
• expectation optimization model
• polynomial-time algorithm

詳細情報

• CRID: 1573668925042970496
• NII論文ID: 10016778182
• NII書誌ID: AA10826272
• ISSN: 09168532
• 本文言語コード: en
• データソース種別:
  • CiNii Articles