A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision making problem

M. A. El Sayed (), Ibrahim A. Baky () and Pitam Singh ()
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M. A. El Sayed: Benha University
Ibrahim A. Baky: Benha University
Pitam Singh: Motilal Nehru National Institute of Technology

OPSEARCH, 2020, vol. 57, issue 4, No 13, 1374-1403

Abstract: Abstract 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 $$ \alpha $$ α -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.

Keywords: Multi-level optimization; Multi-objective programming; TOPSIS; Fractional programming; Chance constrained programming; Fuzzy sets (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s12597-020-00461-w

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