Linear fractional programming for fuzzy random based possibilistic programming problem

Arbaiy, Nureize and Watada, Junzo Linear fractional programming for fuzzy random based possibilistic programming problem. In: 4th International Conference on Computational Intelligence, Modelling and Simulation (CIMSim 2012), 25-27 September 2012, Kuantan, Malaysia.



—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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:component; possibilistic programming; fractional programming; fuzzy random data; vagueness and ambiguity
Subjects:Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Divisions:Faculty of Science Computer and Information Technology > Department of Software Engineering
ID Code:3416
Deposited By:Ms Aryanti Ahmad
Deposited On:15 Jan 2013 11:59
Last Modified:15 Jan 2013 11:59

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