Abstract
AbstractIn this paper a collective choice function (CCF), formulated within a p‐metric distance function framework, is proposed as a generator of several compromise consensuses. Even though, the proposed CCF is not smooth, it is however demonstrated that it can be straightforwardly transformed into easily computable goal programming models. Finally, several cases of individual preferences aggregation are obtained by providing different interpretations of the CCF parameters: ordinal and complete information, ordinal and partial information and a cardinal case through ‘pairwise’ comparison matrices. Copyright © 2009 John Wiley & Sons, Ltd.
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