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2 Foundations of Computing and Decision Sciences

2 1999

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

Leyva-Lopez J. C., Fernandez-Gonzales E.

Foundations of Computing and Decision Sciences

1999

Vol. 24, No. 1

33-47

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.

A fuzzy logic model for bargaining

Espin-Andrade R., Fernandez-Gonzales E.

Foundations of Computing and Decision Sciences

1999

Vol. 24, No. 4

209-218

In this work a fuzzy logic model for bargaining is presented. This model "translates" a group of assumptions obtained from a frequently consulted non mathematical literature, which reflects the experience of prestigious authors about the topic of negotiation , establishing a simple and consensual rationality in contrast with previous approaches. Once this fuzzy mod.el is built, it can be used in connection with the theory of Von Neumann and Morgestem for n-personal games, becoming in a new solution paradigm for these. The model implemented on a MATLAB program can be used as a tool to ease agreement among parts and also to predict the result of the bargaining process.