Clustering is defined as the process of grouping objects that are similar and separating those that are dissimilar. In the field of Multi-Criteria Decision Aid (MCDA) these objects are defined in a richer con-text and compared with respect to the preferences of a Decision Maker(DM). Clustering is closely related to the classical MCDA problems of ranking and sorting. As a result only a few attempts have been made so far at exploring this problem in detail. We model in this article the problem of preferentially ordered clustering using an objective function and propose a method that looks for the optimal result with respect to it. We diversify this objective through an additional property which could be desirable.