A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision making problem
| Autor: | Pitam Singh, M. A. El Sayed, Ibrahim A. Baky |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization 021103 operations research Computer science Rounding Fuzzy set 0211 other engineering and technologies TOPSIS 02 engineering and technology Ideal solution Management Science and Operations Research Fuzzy logic Computer Science Applications Management Information Systems Alpha (programming language) symbols.namesake 020901 industrial engineering & automation Fractional programming Taylor series symbols Information Systems |
| Zdroj: | OPSEARCH. 57:1374-1403 |
| ISSN: | 0975-0320 0030-3887 |
| DOI: | 10.1007/s12597-020-00461-w |
| Popis: | This paper presents a new modified technique for order preference by similarity to ideal solution (M-TOPSIS) approach for unraveling stochastic fuzzy multi-level multi-objective fractional decision making problem (ML-MOFDM) problem. In the proposed model the coefficients and the scalars of the fractional objectives have a fuzzy nature. The right-hand sides are stochastic parameters also, both of the left-hand side coefficients and the tolerance measures are fuzzy kind. In this manner, the deterministic-crisp ML-MOFDM model of stochastic fuzzy ML-MOFDM can be gotten utilizing chance constrained strategy with predominance plausibility criteria and the $$ \alpha $$ -cut methodology. In literature, almost all works on multi-level fractional programming are the crisp version, in which they convert the fractional functions into a linear one using a first order Taylor series which causes rounding off error. The proposed M-TOPSIS approach presents a new method for solving such problem without approximating or changing the nature of the problem. An algorithm to clear up the M-TOPSIS approach, just as illustrative numerical model is displayed. |
| Databáze: | OpenAIRE |
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