2017
DOI: 10.1016/j.asoc.2016.09.021
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An extension of fuzzy TOPSIS for a group decision making with an application to tehran stock exchange

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Cited by 119 publications
(48 citation statements)
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“…For example, Wu et al [2] proposed an improved Analytical Hierarchy Process (AHP) approach to select an optimal financial investment strategy. An extended TOPSIS method was provided by Hatami-Marbini and Kangi [3], and applied in the Tehran stock exchange. Yazdani-Chamzini et al [4] constructed a model on the basis of AHP, decision-making trial and evaluation, and TOPSIS to evaluate investment risk in the private sector of Iran.…”
Section: Introductionmentioning
confidence: 99%
“…For example, Wu et al [2] proposed an improved Analytical Hierarchy Process (AHP) approach to select an optimal financial investment strategy. An extended TOPSIS method was provided by Hatami-Marbini and Kangi [3], and applied in the Tehran stock exchange. Yazdani-Chamzini et al [4] constructed a model on the basis of AHP, decision-making trial and evaluation, and TOPSIS to evaluate investment risk in the private sector of Iran.…”
Section: Introductionmentioning
confidence: 99%
“…TOPSIS method uses all the attribute information, presents the total ranking of the alternatives, while the given attribute preferences may be either dependent or independent [61][62][63][64]. TOPSIS method was applied in this case because it is the best-developed method in this field of multicriteria decision-making problems with simple computation process and high flexibility [65]. Furthermore, there are the following four main reasons [66,67]: (a) TOPSIS logic is rational and understandable; (b) the computation processes are straightforward; (c) this approach presents the best alternatives for each criterion through a mathematical formula; (d) the weights of the criteria are integrated into the procedures for comparison.…”
Section: Characteristic Variablementioning
confidence: 99%
“…In order to minimize the impact of human factors, the target selection in different situations needs to be quantified to make the final choice. In this paper, a TOPSIS decision model based on entropy weight is proposed, which can effectively solve the problem of weight distribution and optimal transportation plan selection [20][21][22][23].…”
Section: Mathematical Modelmentioning
confidence: 99%