A genetic algorithm for deriving final ranking from a fuzzy outranking relation

• Autorzy: Leyva-Lopez J. C. , Fernandez-Gonzales E.
• Języki publikacji: EN

Abstrakty

EN

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

EN

genetic algorithm; fuzzy outranking relation; decision making

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 1999
• Tom: Vol. 24, No. 1
• Strony: 33--47
• Opis fizyczny: Bibliogr. 19 poz.

Twórcy

autor

Leyva-Lopez J. C.

autor

Fernandez-Gonzales E.

• Autonomous University of Sinaloa, Faculty of Engineering Ciudad Universitaria, Culiacan, Sinaloa, Mexico, c.p. 80040,