Ranking the Return on Assets of Tehran Stock Exchange by a New Method Based on Z-Numbers Data

Abstract

Since real-world data are often inaccurate and working with fuzzy data and Z-numbers are very important and necessary, and in the real world, we need to rank and compare data, in this article, we introduce a new method for ranking Z-numbers. This ranking algorithm is based on centroid point. We evaluate the distance between the centroid points, and based on this distance, we rank the Z-numbers. The algorithm of this method has simple calculations and it provides satisfactory results for data in different conditions; we use this method in two practical examples. First, by ranking the return on assets of Tehran stock exchanges, with this method, we can choose the most risky stock and the least risky stock among the available stocks. The advantage of this method over conventional fuzzy methods is considering uncertainty and allocating credit in the opinion of experts to estimate fuzzy parameters, and in the second example, we ranked the factors which affect the productivity of tourism security. Then, by using the proposed algorithm, we introduce the most important and the least important factors for tourist security budgeting.