A Novel Approach for Normal Parameter Reduction Algorithm of Soft Set Using Unit Similarity Matrix

Soft set has been introduced to deal with uncertainty involved in many real life problems. However, most of the time, these decision-making problems involve less important and redundant parameters, which make the decision making process more complex and challenging. Therefore, in this study the concept of reduct of a soft set is discussed and a new algorithm is developed for normal parameter reduction (NPR) base on the unit similarity matrix. Finally, the propose algorithm is compared with previous parameter reduction algorithms in terms of computational complexity