DocumentCode :
1930764
Title :
Linear Fractional Programming for Fuzzy Random Based Possibilistic Programming Problem
Author :
Arbaiy, Nureize ; Watada, Junzo
Author_Institution :
Fac. of Comput. Sci. & Inf. Technol., Univ. Tun Hussein Onn Malaysia, Parit Raja, Malaysia
fYear :
2012
fDate :
25-27 Sept. 2012
Firstpage :
99
Lastpage :
104
Abstract :
The uncertainty in real-world decision making originates from several sources, i.e., fuzziness, randomness, ambiguous. These uncertainties should be included while translating real-world problem into mathematical programming model though handling such uncertainties in the decision making model increases the complexities of the problem and make the solution of the problem hard. 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 multiobjective 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 it´s effectiveness.
Keywords :
decision making; fuzzy set theory; linear programming; mathematical programming; decision making; fuzzy multiobjective linear programming model; fuzzy random environment; linear fractional programming; mathematical programming; multiobjective fuzzy random; possibilistic programming problem; Decision making; Linear programming; Mathematical model; Mathematical programming; Possibility theory; Programming; Uncertainty; fractional programming; fuzzy random data; possibilistic programming; vagueness and ambiguity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on
Conference_Location :
Kuantan
ISSN :
2166-8531
Print_ISBN :
978-1-4673-3113-5
Type :
conf
DOI :
10.1109/CIMSim.2012.42
Filename :
6338053
Link To Document :
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