ID | 115814 |
著者 |
Katagiri, Hideki
Kanagawa University
Kato, Kosuke
Hiroshima Institute of Technology
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キーワード | discrete fuzzy random variable
linear programming
possibility measure
necessity measure
expectation model
Pareto optimal solution
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資料タイプ |
学術雑誌論文
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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.
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掲載誌名 |
Symmetry
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ISSN | 20738994
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出版者 | MDPI
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巻 | 9
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号 | 11
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開始ページ | 254
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発行日 | 2017-10-30
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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/).
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言語 |
eng
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著者版フラグ |
出版社版
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部局 |
理工学系
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