Building multi-objective fuzzy random programming model

Nureize Arbaiy, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)


    A real-life application faces various kinds of inherent uncertainties which occurs simultaneously. To find solution, formulating real world problem into mathematical programming model is challenging. Uncertain parameters in a problem model can be characterized as vagueness, ambiguous and random of the information. Such uncertainties make the existing multi-objective model incapable of handling such situations. Thus, in this paper we present the multi-objective decision model from the perspective of possibilistic programming approach to scrutinize the uncertainties in the decision making. The proposed concept can be used to build model for multi-objective problem which is exposed with various types of uncertainties. We include an illustrative example to explain the model, and highlight its advantages.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Fuzzy Systems
    Publication statusPublished - 2013
    Event2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad
    Duration: 2013 Jul 72013 Jul 10


    Other2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013


    • Fuzzy random coefficient
    • Multi-objective evaluation
    • Necessity measure
    • Possibilistic programming

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence
    • Applied Mathematics
    • Theoretical Computer Science


    Dive into the research topics of 'Building multi-objective fuzzy random programming model'. Together they form a unique fingerprint.

    Cite this