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- Paula Sarabando, Luis C. Dias
- IEEE Trans. Systems, Man, and Cybernetics, Part A
- 2009

In the context of additive multiattribute aggregation, we address problems with ordinal information, i.e., considering a ranking of the weights (the scaling coefficients). Several rules for ranking alternatives in these situations have been proposed and compared, such as the rank-order-centroid weight, minimum value, central value, and maximum regret rules.… (More)

- Paula Sarabando, Luis C. Dias
- Computers & OR
- 2010

The additive model of multiattribute value (or utility) theory is widely used in multicriteria choice problems. However, often it is not easy to obtain precise values for the scaling weights or the alternatives’ value in each function. Several decision rules have been proposed to select an alternative under these circumstances, which require weaker… (More)

In bilateral Negotiation Analysis, the literature often considers the case of complete information. In this context, since the negotiators know the value functions of both parties, it is not difficult to calculate the Pareto frontier and the Pareto efficient solutions for the negotiation. Thus rational negotiators can reach agreement on this frontier.… (More)

- Luis C. Dias, Paula Sarabando
- Decision Analysis
- 2012

K Arrow’s work on social welfare proposed a set of conditions that a function to aggregate ordinal preferences of the members of a group should satisfy, proving that it was not possible to satisfy all these assumptions simultaneously. Later, Ralph Keeney adapted these conditions and proposed a cardinal utility axiomatization for the problem of aggregating… (More)

- Rudolf Vetschera, Paula Sarabando, Luis C. Dias
- Computers & OR
- 2014

We present a comprehensive computational study on the effects of providing different forms of incomplete preference information in additive group decision models. We consider different types of information on individual preferences, and on weights of the group members, and study their effects on conclusiveness, efficiency and fairness of outcomes at the… (More)

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