Cooperative two-level nonlinear programming through particle swarm optimization and its fuzzy stochastic extensions

2018 Fiscal Year Final Research Report

• Project/Area Number: 16K01244
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Social systems engineering/Safety system
• Research Institution: Gunma University (2017-2018); Hiroshima University (2016)
• Principal Investigator: Matsui Takeshi 群馬大学, 社会情報学部, 准教授 (50512505)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: 2レベル計画法 / 協力関係 / 粒子群最適化 / ファジィ計画法 / 確率計画法

Outline of Final Research Achievements

Was the formulation of the two-level programming problems in fuzzy random environment that takes into account the fuzziness and randomness of the reality of the decision-making situation. Furthermore, not only the fuzziness included in the parameter of the modeling process, considering ambiguity of judgment as a human decision maker simultaneously, was developed Interactive Fuzzy decision method of human-centered. A high-speed and high-precision approximation method has been constructed by proposing a particle swarm optimization method that efficiently searches for the optimality for finding an extended satisfactory solution considering the fuzziness. Further, it addresses the planning problem in the real system as an application of the real decision problem with trying to formulate were derived of satisfactory solution by particle swarm optimization technique.

Free Research Field

オペレーションズ・リサーチ

Academic Significance and Societal Importance of the Research Achievements

現実のさまざまな意思決定状況おける不確実性を考慮したファジィ・ランダム環境における2レベル非線形計画法の提案により，ファジィ数の実現値が確率的に変動するファジィランダム2レベル非線形計画法のみならず，平均や分散がファジィ数であるようなランダムファジィ2レベル非線形計画法が確立され，産業界における幅広い活用が容易になる．
また，現実の意思決定状況への幅広い応用．産業界における実システムの一例として，地域冷暖房システムにおける計画問題を取り上げ，不確実環境下での計画問題としての定式化を試みることにより，より幅広い意思決定者からの支持を受けることが期待される．