Soft dominance based rough sets with applications in information systems

Abstract

Classical rough set theory is considered as a useful mathematical tool to deal with the uncertainty of categorical data; a major deficiency of this model is its sensitivity to noise in classification learning due to the strong condition of equivalence relation. Meanwhile decision making can be considered as a mental process in which human beings make a choice among several alternatives. However, with the increasing complexity of real decision making problems, the decision makers frequently face the challenge of characterizing their preferences in an uncertain context. In the present paper, we initiate multi-attribute group decision making problems in the presence of multi-attribute and multi-decision decision making with preferences. We present the concept of soft preference relation and soft dominance relation corresponding to a decision attribute in multi-criteria and multi-decision information system. Further we present the idea of soft dominance rough sets and their applications in solving a multi-agent conflict analysis decision problem. The proposed method addresses the limitations of the Pawlak model and Sun's conflict analysis model and thus improve these models. Finally, the experimental results on labor management negotiation problems show that the proposed algorithms are more effective and efficient for feasible consensus strategy when compared with Sun's technique.