Random fuzzy multi-objective linear programming: Optimization of possibilistic value at risk (pVaR)

► We tackle a new multiobjective programming problem with random fuzzy variables. ► We propose a new model optimizing possibilistic value at risk, called pVaR. ► We prove that the original problem can be transformed into a deterministic problem. ► We provide an interactive algorithm to obtain a sati...

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Veröffentlicht in:	Expert systems with applications Jg. 40; H. 2; S. 563 - 574
Hauptverfasser:	Katagiri, Hideki, Uno, Takeshi, Kato, Kosuke, Tsuda, Hiroshi, Tsubaki, Hiroe
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 01.02.2013 Elsevier
Schlagworte:	Applied sciences Decision theory. Utility theory Exact sciences and technology Fuzzy Fuzzy logic Fuzzy set theory Interactive algorithm Mathematical analysis Mathematical models Mathematical programming Multiobjective linear programming Necessity Operational research and scientific management Operational research. Management science Optimization Pareto optimal solution Pareto optimality Portfolio theory Possibilistic value at risk (pVaR) Possibility Random fuzzy variable Risk Risk theory. Actuarial science Possibilistic value at risk (pVaR) Interactive algorithm Necessity Pareto optimal solution Multiobjective linear programming Possibility Random fuzzy variable Multiobjective programming Financial management Convex programming Optimization Uncertain system Possibility theory Angular distribution Deterministic approach Quantile Random variable Interactive programming Warranty Probabilistic approach Pareto optimum Decision support system Decision making Linear programming Fuzzy programming Risk analysis Fuzzy logic Optimal solution Objective function Risk management Portfolio management
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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