Linear fractional programming for fuzzy random based possibilistic programming problem

Nureize Binti Arbaiy; Junzo Watada

doi:10.1109/CIMSim.2012.42

Linear fractional programming for fuzzy random based possibilistic programming problem

Nureize Binti Arbaiy^*, Junzo Watada

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of International Conference on Computational Intelligence, Modelling and Simulation
Pages	99-104
Number of pages	6
DOIs	https://doi.org/10.1109/CIMSim.2012.42
Publication status	Published - 2012
Event	4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012 - Kuantan, Malaysia Duration: 2012 Sept 25 → 2012 Sept 27

Other

Other	4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012
Country/Territory	Malaysia
City	Kuantan
Period	12/9/25 → 12/9/27

Keywords

Fractional programming
Fuzzy random data
Possibilistic programming
Vagueness and ambiguity

ASJC Scopus subject areas

Computational Theory and Mathematics
Applied Mathematics
Modelling and Simulation

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10.1109/CIMSim.2012.42

Cite this

Arbaiy, NB & Watada, J 2012, Linear fractional programming for fuzzy random based possibilistic programming problem. in Proceedings of International Conference on Computational Intelligence, Modelling and Simulation., 6338053, pp. 99-104, 4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012, Kuantan, Malaysia, 12/9/25. https://doi.org/10.1109/CIMSim.2012.42

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title = "Linear fractional programming for fuzzy random based possibilistic programming problem",

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.",

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language = "English",

pages = "99--104",

booktitle = "Proceedings of International Conference on Computational Intelligence, Modelling and Simulation",

note = "4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012 ; Conference date: 25-09-2012 Through 27-09-2012",

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AU - Watada, Junzo

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AB - 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.

KW - Fractional programming

KW - Fuzzy random data

KW - Possibilistic programming

KW - Vagueness and ambiguity

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Linear fractional programming for fuzzy random based possibilistic programming problem

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Keywords

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