Interactive evolutionary multiobjective optimization using dominance-based rough set approach

Salvatore Greco, B. Matarazzo, R. Slowinski

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


    We present basic ideas related to application of Dominance-based Rough Set Approach (DRSA) in interactive Evolutionary Multiobjective Optimization (EMO). In the proposed methodology, the preference information elicited by the decision maker in successive iterations consists in sorting some solutions in the current population into "relatively good" and "others", or in comparing some pairs of solutions with respect to preference. The "if ..., then ..." decision rules are then induced from this preference information using Dominance-based Rough Set Approach (DRSA). These rules are used within EMO in order to focus on populations of solutions satisfying the preferences of the decision maker, speeding up convergence to the most preferred region of the Pareto-front. The resulting interactive schemes, corresponding to the two types of preference information, are called DRSA-EMO and DRSA-EMO-PCT, respectively. The proposed methodology permits also to take into account robust concerns in multiobjective optimization.
    Original languageEnglish
    Title of host publicationIEEE congress on evolutionary computation 2010
    Place of PublicationPiscataway
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages8
    ISBN (Print)9781424469093
    Publication statusPublished - 2010


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