We present the methodology of Multiple-Criteria Decision Aiding (MCDA) based on preference modelling in terms of “if..., then ...” decision rules. The basic assumption of the decision rule approach is that the decision maker (DM) accepts to give preferential information in terms of examples of decisions and looks for simple rules justifying her decisions. An important advantage of this approach...

Ordinal classification problems with monotonicity constraints (also referred to as multicriteria classification problems) often appear in real-life applications, however, they are considered relatively less frequently in theoretical studies than regular classification problems. We introduce a rule induction algorithm based on the statistical learning approach that is tailored for this type of p...

In this paper we study optimization problems with second-order stochastic dominance constraints. This class of problems has been receiving increasing attention in the literature as it allows for the modeling of optimization problems where a risk-averse decision maker wants to ensure that the solution produced by the model dominates certain benchmarks. Here we deal with the case of multi-variate...

Promising growth rates, increased trade, and competition among major global players for African resources have boosted the development and bargaining power of sub-Saharan Africa (SSA) in relation to the EU. However, Africa's least developed countries remain vulnerable to external shocks. Academic analysis is still too heavily influenced by scholastic controversies. Neither the controversy over ...

Scientific analysis of decision problems aims at giving the decision maker (DM) a recommendation concerning a set of objects (called also alternatives, solutions, acts, actions, cases, candidates) evaluated from the point of view of a plurality of their characteristics considered relevant for the problem at hand, and called attributes. For example, a decision can regard: 1) diagnosis of patholo...

Lower and upper approximations of upward (downward) union of decision classes in Variable Consistency Dominance-Based Rough Set Approach (VC-DRSA) are the basis for extraction of decision rules, so computations of approximations is a necessary step in knowledge representing and reduction based on VCDRSA. In this paper, a matrix-based method for computing lower approximations of upward and downw...

Set-valued information systems are generalized models of single-valued information systems. Its semantic interpretation can be classified into two categories: disjunctive and conjunctive. We focus on the former in this paper. By introducing four types of dominance relations to the disjunctive set-valued information systems, we establish a dominance-based rough sets approach, which is mainly bas...

objectives: mastectomy as a treatment for breast cancer can disturb marital satisfaction of many couples. in this way, existential anxieties stemming from this potentially deleterious event, and inefficient responses to them, could be mediating. the purpose of this study is to investigate the effectiveness of a rehabilitation method based on existential approach and olson's marital enrichm...

The rough set theory was proved of its effectiveness in dealing with the imprecise and ambiguous information. Dominance-based Rough Set Approach (DRSA), as one of the extensions, is effective and fundamentally important for Multiple Criteria Decision Analysis (MCDA). However, most of existing DRSA models cannot directly examine uncertain information within rough boundary regions, which might mi...

We present a methodology for non-statistical preference learning in multicriteria ranking based on Variable Consistency Dominance-based Rough Set Approach (VC-DRSA). A finite set of objects to be ranked is evaluated by a set of criteria, which are real-valued functions with ordinal or cardinal scales. Given the statement of a multicriteria ranking problem, the only objective information one can...