Abstract
The generalized interval-valued trapezoidal fuzzy best-worst method (GITrF-BWM) provides more reliable and more consistent criteria weights for multiple criteria group decision making (MCGDM) problems. In this study, GITrF-BWM is integrated with the extended TOPSIS (technique for order preference by similarity to the ideal solution) and extended VIKOR (visekriterijumska optimizacija i kompromisno resenje) methods for the selection of the optimal industrial robot using fuzzy information. For a criteria-based selection process, assigning weights play a vital role and significantly affect the decision. Assigning weights based on direct opinions of decision makers can be biased, so weight deriving models, such as GITrF-BWM, overcome this discrepancy. In previous studies, generalized interval-valued trapezoidal fuzzy weights were not derived by using any MCGDM method for the robot selection process. For this study, both subjective and objective criteria are considered. The preferences of decision makers are provided with the help of linguistic terms that are then converted into fuzzy information. The stability and reliability of the methods were tested by performing sensitivity analysis, which showed that the ranking results of both the methodologies are not symmetrical, and the integration of GITrF-BWM with the extended TOPSIS method provides stable and reliable results as compared to the integration of GITrF-BWM with the extended VIKOR method. Hence, the proposed methodology provides robust optimal industrial robot selection.
Highlights
Nowadays, the decision-making process includes subjective and uncertain criteria for the selection procedure
Sensitivity analysis was performed with respect to criteria; the results showed that GITrF-TOPSIS was more sensitive with respect to c2 and c3, and GITrF-visekriterijumska optimizacija i kompromisno resenje (VIKOR) was more sensitive with respect to c2, c3, c5 and c6
Robot selection multiple criteria group decision making (MCGDM) problems were discussed with regards to two hybrid methodologies: (1) GITrF-best-worst method (BWM) with GITrF-TOPSIS and (2) GITrF-BWM with GITrF-VIKOR
Summary
The decision-making process includes subjective and uncertain criteria for the selection procedure. The market is full of industrial robots with various types of special features of industrial work, including many specifications and related skills In such situations, industries require an expert team of decision makers in the selection process of robots that are suitable for a particular production and application. Decision makers provided their preferences using linguistic terms They felt more comfortable giving opinions using linguistic terms; the more reliable and consistent generalized interval-valued trapezoidal fuzzy weights (GITrFWs) were calculated using GITrF-BWM. Experts provided their preferences about the alternatives with respect to each subjective criteria using linguistic terms that were converted into the GITrFNs. The provided fuzzy information was aggregated and normalized, and using GITrFWs, fuzzy information was converted to a weighted normalized form.
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