直近一年間の累計
アクセス数 : ?
ダウンロード数 : ?
ID 115814
著者
Katagiri, Hideki Kanagawa University
Kato, Kosuke Hiroshima Institute of Technology
キーワード
discrete fuzzy random variable
linear programming
possibility measure
necessity measure
expectation model
Pareto optimal solution
資料タイプ
学術雑誌論文
抄録
This paper considers linear programming problems (LPPs) where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables). New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
掲載誌名
Symmetry
ISSN
20738994
出版者
MDPI
9
11
開始ページ
254
発行日
2017-10-30
権利情報
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
EDB ID
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
理工学系