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The multiple criteria aggregation methods allow us to construct a prescription (or solution) from a set of alternatives based on the preferences of a Decision Maker or a group of Decision Makers. In some approaches, the prescription is immediately deduced from the aggregation preferences process. When the aggregation model of preferences is based on the outranking approach, a special treatment is required, but some non rational violations of the explicit global model of preferences could happen. In this paper a new genetic algorithm which allows to exploit a known fuzzy outranking relation is introduced with the purpose of constructing a prescription for ranking problems. The performance of our algorithm is evaluated on a set of test problems. Computational results show that the genetic a1gorithrn-based heuristic is capable of producing high-quality prescriptions.
Słowa kluczowe
Rocznik
Tom
Strony
33--47
Opis fizyczny
Bibliogr. 19 poz.
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autor
autor
- Autonomous University of Sinaloa, Faculty of Engineering Ciudad Universitaria, Culiacan, Sinaloa, Mexico, c.p. 80040, jleyva@uas.uasnet.mx
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Bibliografia
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bwmeta1.element.baztech-article-BPP1-0011-0083