抄録
The uncertainty in real-world decision making originates from several sources, i.e., fuzziness, randomness, ambiguity. These uncertainties exist in the problem description and in the preference information in the mathematical programming model. Handling such uncertainties in the decision making model increases the complexities of the problem and make the solution of the problem is difficult to solve. In this paper, a linear fractional programming is used to solve multi-objective fuzzy random based possibilistic programming problems to address the vague decision maker's preference (aspiration) and ambiguous data (coefficient), in a fuzzy random environment. The developed model plays a vital role in the construction of fuzzy multi-objective linear programming model, which is exposed to various types of uncertainties that should be treated properly. An illustrative example explains the developed model and highlights its effectiveness.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 26-32 |
| ページ数 | 7 |
| ジャーナル | International Journal of Simulation: Systems, Science and Technology |
| 巻 | 15 |
| 発行部数 | 1 |
| 出版物ステータス | Published - 2014 |
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ASJC Scopus subject areas
- Software
- Modelling and Simulation
これを引用
Linear fractional programming for fuzzy random based possibilistic programming problem. / Arbaiy, Nureize; Watada, Junzo.
：: International Journal of Simulation: Systems, Science and Technology, 巻 15, 番号 1, 2014, p. 26-32.研究成果: Article
}
TY - JOUR
T1 - Linear fractional programming for fuzzy random based possibilistic programming problem
AU - Arbaiy, Nureize
AU - Watada, Junzo
PY - 2014
Y1 - 2014
N2 - The uncertainty in real-world decision making originates from several sources, i.e., fuzziness, randomness, ambiguity. These uncertainties exist in the problem description and in the preference information in the mathematical programming model. Handling such uncertainties in the decision making model increases the complexities of the problem and make the solution of the problem is difficult to solve. In this paper, a linear fractional programming is used to solve multi-objective fuzzy random based possibilistic programming problems to address the vague decision maker's preference (aspiration) and ambiguous data (coefficient), in a fuzzy random environment. The developed model plays a vital role in the construction of fuzzy multi-objective linear programming model, which is exposed to various types of uncertainties that should be treated properly. An illustrative example explains the developed model and highlights its effectiveness.
AB - The uncertainty in real-world decision making originates from several sources, i.e., fuzziness, randomness, ambiguity. These uncertainties exist in the problem description and in the preference information in the mathematical programming model. Handling such uncertainties in the decision making model increases the complexities of the problem and make the solution of the problem is difficult to solve. In this paper, a linear fractional programming is used to solve multi-objective fuzzy random based possibilistic programming problems to address the vague decision maker's preference (aspiration) and ambiguous data (coefficient), in a fuzzy random environment. The developed model plays a vital role in the construction of fuzzy multi-objective linear programming model, which is exposed to various types of uncertainties that should be treated properly. An illustrative example explains the developed model and highlights its effectiveness.
KW - Component
KW - Fractional programming
KW - Fuzzy random data
KW - Possibilistic programming
KW - Vagueness and ambiguity
UR - http://www.scopus.com/inward/record.url?scp=84906098080&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84906098080&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84906098080
VL - 15
SP - 26
EP - 32
JO - International Journal of Simulation: Systems, Science and Technology
JF - International Journal of Simulation: Systems, Science and Technology
SN - 1473-804X
IS - 1
ER -