Improving decision making approaches based on fuzzy soft sets and rough soft sets

Abstract

Hybrid soft sets, such as fuzzy soft sets and rough soft sets, have been extensively applied to decision making. However in both cases, there is still a necessity of providing improvements on approaches to obtain better decision results in different situations. In this paper several proposals for decision making are provided based on both hybrid soft sets. For fuzzy soft sets, a computational tool called D-score table is introduced to improve the decision process of a classical approach and its convenience has been proved when attributes change across the decision process. In addition, a novel adjustable approach based on decision rules is introduced. Regarding rough soft sets, several new decision algorithms to meet different decision makers’ requirements are introduced together a multi-criteria group decision making approach. Several practical examples are developed to show the validity of such proposals.