| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 387843 | Expert Systems with Applications | 2009 | 7 Pages |
Abstract
This work suggests a fuzzy TOPSIS model, where ratings of alternatives under criteria and importance weights of criteria are assessed in linguistic values represented by fuzzy numbers. Criteria can be categorized into benefit and cost. Ratings of alternatives versus criteria and the importance weights of criteria are normalized before multiplication. The membership function of each fuzzy weighted rating can be developed by interval arithmetic of fuzzy numbers. A ranking method can then be applied easily to develop positive and negative idea solutions in order to complete the fuzzy TOPSIS model. Finally, a numerical example demonstrates the feasibility of the proposed method.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ta-Chung Chu, Yi-Chen Lin,