Linear fractional programming for fuzzy random based possibilistic programming problem

Nureize Arbaiy, Junzo Watada

    研究成果: Article

    5 引用 (Scopus)

    抄録

    The uncertainty in real-world decision making originates from several sources, i.e., fuzziness, randomness, ambiguity. These uncertainties exist in the problem description and in the preference information in the mathematical programming model. Handling such uncertainties in the decision making model increases the complexities of the problem and make the solution of the problem is difficult to solve. 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 multi-objective 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 its effectiveness.

    元の言語English
    ページ(範囲)26-32
    ページ数7
    ジャーナルInternational Journal of Simulation: Systems, Science and Technology
    15
    発行部数1
    出版物ステータスPublished - 2014

    Fingerprint

    Fractional Programming
    Programming
    Uncertainty
    Programming Model
    Decision Making
    Multiobjective Linear Programming
    Fuzzy Linear Programming
    Decision making
    Random Environment
    Fuzziness
    Ambiguous
    Mathematical Programming
    Randomness
    Mathematical programming
    Linear Model
    Linear programming
    Model
    Mathematical Model
    Coefficient

    ASJC Scopus subject areas

    • Software
    • Modelling and Simulation

    これを引用

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