Many fuzzy number ranking approaches are developed in the literature for multiattribute decision-making problems. Almost all of the existing approaches focus on quantity measurement of fuzzy numbers for ranking purpose. In this paper, we consider the ranking process to determine a decision-maker's p
Investors’ preference order of fuzzy numbers
✍ Scribed by Hsuan-Ku Liu; Berlin Wu; Ming Long Liu
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 321 KB
- Volume
- 55
- Category
- Article
- ISSN
- 0898-1221
No coin nor oath required. For personal study only.
✦ Synopsis
Nowadays greater and greater realistic financial problems are modeled by using the stochastic programming in the fuzzy environment. Hence, ranking a set of fuzzy numbers that is consistent with the investors' preference becomes important for modelling a realistic problem. In this paper, we will provide a new ranking procedure that is consistent with the preference of the conservative investors. Our ranking procedure satisfies the axioms of three order relations for the separable fuzzy numbers or the triangle fuzzy numbers. We found that our ranking procedure has a better capability of discriminating the order of two fuzzy numbers. For the LR-type fuzzy numbers, our ranking procedure reduces the computational time substantially.
📜 SIMILAR VOLUMES
We propose a ranking method for fuzzy numbers. In this method a preference function is deÿned by which fuzzy numbers are measured point by point and at each point the most preferred number is identiÿed. Then, these numbers are ranked on the basis of their preference ratio. Therefore, fuzzy numbers a
In this paper, we extend the conventional fuzzy numbers and introduce a new fuzzy number system named vector space of ordered pairs (VSOP). Then, we axiomatically define the fuzzy comparison relations (>-, ' L-\_ and \_~) on VSOP starting from the requirements of fuzzy ordering and vector ordering.