An evidential reasoning based approach for decision making with partially ordered preference under uncertainty

Shuwei Chen, Jun Liu, Hui Wang, Juan Carlos Augusto

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    8 Citations (Scopus)

    Abstract

    In many cases, decision making is to order alternatives and select one or a few among the top of the ranking based on decision makers' preferences. Due to the complexity and flexibility of reality, decision makers usually can only provide partially ordered preferences with certain belief degrees. In order to deal with this kind of decision making problem, we introduce in this paper the use a belief structure for representing the involved partially ordered preferences with belief degrees, then a preference combination approach based on evidential reasoning is proposed to combine the preferences from different decision makers. The final ranking of alternatives is generated based on a distance measure between pairs of preference relations. An illustrative example is provided to show the rationality of the proposed method.

    Original languageEnglish
    Title of host publicationProceedings - International Conference on Machine Learning and Cybernetics
    PublisherIEEE Computer Society
    Pages1712-1717
    Number of pages6
    ISBN (Electronic)9781479902576
    DOIs
    Publication statusPublished - 2013
    Event12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 - Tianjin, China
    Duration: 14 Jul 201317 Jul 2013

    Publication series

    NameProceedings - International Conference on Machine Learning and Cybernetics
    Volume4
    ISSN (Print)2160-133X
    ISSN (Electronic)2160-1348

    Conference

    Conference12th International Conference on Machine Learning and Cybernetics, ICMLC 2013
    CountryChina
    CityTianjin
    Period14/07/1317/07/13

    Keywords

    • Belief Degree
    • Decision Making
    • Distance Measure
    • Evidential Reasoning
    • Preference

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