Fuzzy Aggregation for Ranking in Business

Abstract

Today, businesses depend strongly on data and the opinion of customers or the experience of managers or experts. The large databases contain non-heterogeneous data, which is the ground for further decisions. Business uses multicriterial decisions in more areas (e.g., customer care, marketing, product development, risk management, HR, etc.) and often it is based on assessment. One of the assessment methods is the ranking, which can be done by crisp values of data where the sharp borders between evaluated entities do not give the adequate ranking result. On the other hand, the ranking process is based on the qualitative assessment, which has linguistic expression. It is more familiar and understandable for people. The article shows how to treat non-heterogeneous data to prepare them for a ranking process using fuzzy sets theory. The article aims at offering several types of ranking methods based on different inputs and preferences of the user and describes appropriate fuzzy aggregations for solving the ranking problem.

Trident Fuzzy Aggregation Operators on Right and Left Apex-Base Angles in Parallel Computing

“…Archimedian t-norm and t-conorm built combination operatives for hexagonal fuzzy numbers along with the method of refining instruction. Moreover, fuzzy aggregation for ranking in business [13].Methodology for computing applications can be implemented for the networking optimization of various applications [14] [15]. This study includes the following sections: preliminaries, fuzzy aggregation, proposed method: Trident fuzzy aggregation,right andleft apex-base angle for trapezoidal trident fuzzy number, and the Geometric mean over 'n' trapezoidal trident fuzzy numbers for left-side and right-side apex-base angle and lastly, the deduction is constructed.…”