A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set

We present two innovations that produce a novel approach to the problem of fuzzy soft set based decision making in the presence of multiobserver input parameter data sets. The first novelty consists of a new process of information fusion that furnishes a more reliable resultant fuzzy soft set from such input data set. The second one concerns the mechanism that decides among the alternatives in this resultant fuzzy soft set. It relies on scores computed from a relative Comparison matrix. The advantages of our novel procedure are a higher power of discrimination and a well-determined final solution.