Multi-attribute classification (ordering) problem concerns assignment of objects (tasks) to some predefined and preference-ordered decision classes [1, 2]. In considered situation objects are described by a finite sets of locations. Disposing several objects ranking lists it is possible exploit information about distribution. It was assumed that distribution information base on so called neighborhoods structures. These structures can approve or disapprove judgments unanimity prepared by experts (agents, responders, algorithms). Disposing distribution characteristics we define set of criteria. So, it is challenging problem which can be solved on base of preference theory. Reaching preference approach by neighborhood elements we exploit addition information, which help compromise achievement. Proposed method of objects ordering based of considering preference relations during process of lists combining up along their positions. Such approach enlarge scale of divergences in these relations.
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