Multi-level multi-objective decision problem through fuzzy random regression based objective function

Nureize Arbaiy*, Junzo Watada

*Corresponding author for this work

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

    4 Citations (Scopus)

    Abstract

    A multi-level decision making problem confronts several issues especially in coordinating decision in hierarchic processes and in compromising conflicting objectives for each decision level. Therefore, its mathematical model plays a pivotal role in solving such problem, and is influencing to the final result. However, it is sometimes difficult to estimate the coefficients of objective functions of the model in real situations specifically when the statistical data contain random and fuzzy information. Thus, decision making scheme should provide an appropriate method to handle the presence of such uncertainties. Hence, this paper proposes a fuzzy random regression method to estimate the coefficients value for the objective functions of multi-level multi-objective model. The algorithm is constructed to obtain a satisfaction solution, which fulfills at least weak Pareto optimality. A numerical example illustrates the proposed solution procedure.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Fuzzy Systems
    Pages557-563
    Number of pages7
    DOIs
    Publication statusPublished - 2011
    Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei
    Duration: 2011 Jun 272011 Jun 30

    Other

    Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
    CityTaipei
    Period11/6/2711/6/30

    Keywords

    • additive fuzzy goal programming
    • fuzzy random regression model
    • multi-level problem
    • multi-objective

    ASJC Scopus subject areas

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

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