Linear fractional programming for fuzzy random based possibilistic programming problem

Nureize Binti Arbaiy, Junzo Watada

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ホスト出版物のタイトルProceedings of International Conference on Computational Intelligence, Modelling and Simulation
    ページ99-104
    ページ数6
    DOI
    出版ステータスPublished - 2012
    イベント4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012 - Kuantan, Malaysia
    継続期間: 2012 9 252012 9 27

    Other

    Other4th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2012
    CountryMalaysia
    CityKuantan
    Period12/9/2512/9/27

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Applied Mathematics
    • Modelling and Simulation

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