Parameter reduction of intuitionistic fuzzy soft sets and its related algorithms

Abstract

Contribution of intuitionistic fuzzy soft set (IFSS) in uncertain real-life applications is inevitable. Computation with IFSS may be complicated by the use of less important parameters. However, there has been a little focus on parameter reduction of IFSSs. In this paper, we introduce two different parameter reduction algorithms in IFSSs to satisfy the different needs of decision makers. The first algorithm is based on selection of a set of parameters whose combined contribution is less important in the decision-making process. The second approach selects parameter(s) which has less deviation in comparison to the other parameters. Finally, the proposed algorithms have been demonstrated using illustrative numerical examples. This study also preserves the decision abilities while reducing the redundant parameters.