Name
Abstract | ||
|---|---|---|
Decision making is the process of finding the best option among the feasible alternatives. In classical multiple attribute decision making (MADM) methods, the ratings and the weights of the criteria are known precisely. Due to vagueness of the decision data, the crisp data are inadequate for real-life situations. Since human judgments including preferences are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in decision making is deemed to be relevant. We design a model of TOPSIS for the fuzzy environment with the introduction of appropriate negations for obtaining ideal solutions. Here, we apply a new measurement of fuzzy distance value with a lower bound of alternatives. Then similarity degree is used for ranking of alternatives. Examples are shown to demonstrate capabilities of the proposed model. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.amc.2008.05.047 | Applied Mathematics and Computation |
Keywords | Field | DocType |
TOPSIS,Triangular fuzzy number,MADM,Fuzzy distance | Vagueness,Mathematical optimization,Multiple criteria,Ranking,Upper and lower bounds,Fuzzy logic,Ideal solution,Weighted sum model,TOPSIS,Mathematics | Journal |
Volume | Issue | ISSN |
206 | 2 | 0096-3003 |
Citations | PageRank | References |
38 | 1.76 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iraj Mahdavi | 1 | 388 | 32.30 |
| Nezam Mahdavi-amiri | 2 | 371 | 39.95 |
| Armaghan Heidarzade | 3 | 83 | 5.16 |
| Rahele Nourifar | 4 | 56 | 2.52 |