A novel parameter reduction method for fuzzy soft sets

Abstract

Fuzzy soft set as a tool to deal with uncertainty can effectively handle decision making problems. However, there are many redundant parameters in the decision making process. In order to remove redundant parameters to improve the efficiency of decision making, different parameter reduction algorithms for fuzzy soft sets based on different decision criteria have been proposed. This paper focuses on the problem of parameter reduction of fuzzy soft sets based on choice value criteria. The restrictions of the strict conditions about parameter reduction lead to a very low applicability of some previous algorithms based on choice value criteria. To address this limitation, we introduce a flexible definition of parameter reduction for fuzzy soft sets. Further a difference-based parameter reduction algorithm for fuzzy soft sets is proposed. Compared with some previous algorithms based on choice value criteria, the proposed algorithm not only has wider applicability, but also can reduce more redundant parameters making the found parameter reduction with a lower cardinality, and it is easier to find the parameter reduction of fuzzy soft sets.