Spinning preparation parameters selection for rotor spun knitted fabric using VIKOR method of multicriteria decision-making

2013 ◽  
Vol 104 (1) ◽  
pp. 7-17 ◽  
Author(s):  
A.R. Fallahpour ◽  
A.R. Moghassem
Author(s):  
Luisa Andrea González-Cruz ◽  
Luis Fernando Morales-Mendoza ◽  
Alberto Alfonso Aguilar-Lasserre ◽  
Catherine Azzaro-Pantel ◽  
Paulina Martínez-Isidro ◽  
...  

Author(s):  
Leoni Pentiado Godoy ◽  
Natalia Pedroso Serpa ◽  
André Brum Missaggia ◽  
Roger Da Silva Wegner ◽  
Julio Siluk ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Rui Yong ◽  
Jun Ye ◽  
Shigui Du

The information expression and modeling of decision-making are critical problems in the fuzzy decision theory and method. However, existing trapezoidal neutrosophic numbers (TrNNs) and neutrosophic Z-numbers (NZNs) and their multicriteria decision-making (MDM) methods reveal their insufficiencies, such as without considering the reliability measures in TrNN and continuous Z-numbers in NZN. To overcome the insufficiencies, it is necessary that one needs to propose trapezoidal neutrosophic Z-numbers (TrNZNs), their aggregation operations, and an MDM method for solving MDM problems with TrNZN information. Hence, this study first proposes a TrNZN set, some basic operations of TrNZNs, and the score and accuracy functions of TrNZN and their ranking laws. Then, the TrNZN weighted arithmetic averaging (TrNZNWAA) and TrNZN weighted geometric averaging (TrNZNWGA) operators are presented based on the operations of TrNZNs. Next, an MDM approach using the proposed aggregation operators and score and accuracy functions is established to carry out MDM problems under the environment of TrNZNs. In the end, the established MDM approach is applied to an MDM example of software selection for revealing its rationality and efficiency in the setting of TrNZNs. The main advantage of this study is that the established approach not only makes assessment information continuous and reliable but also strengthens the decision rationality and efficiency in the setting of TrNZNs.


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