Multiobjective random fuzzy linear programming problems based on the possibility maximization model

Takashi Hasuike*, Hideki Katagiri, Hiroaki Ishii

*この研究の対応する著者

研究成果: Article査読

10 被引用数 (Scopus)

抄録

Two multiobjective random fuzzy programming problems considered based on the possibility maximization model using possibilistic and stochastic programming are not initially well defined due to the random variables and fuzzy numbers included. To solve them analytically, probability criteria are set for objective functions and chance constraints are introduced. Taking into account the decision maker's subjectivity and the original plan's flexibility, a fuzzy goal is introduced for each objective function. The original problems are then changed into deterministic equivalent problems to make the possibility fractile optimization problem equivalent to a linear programming problem. The possibility maximization problem for probability is changed into a nonlinear programming problem, and an analytical solution is constructed extending previous solution approaches.

本文言語English
ページ(範囲)373-379
ページ数7
ジャーナルJournal of Advanced Computational Intelligence and Intelligent Informatics
13
4
DOI
出版ステータスPublished - 2009 1 1
外部発表はい

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • 人工知能

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