Extensions, integrations and applications of best worst method
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Date
2022-04-01
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UMT Lahore
Abstract
This research consists of two-part; one is the extensions of the classical Best-Worst Method (BWM) in the context of hesitant fuzzy information and generalized interval-valued trapezoidal fuzzy (GITrF) information, and the other is the applications of classical and fuzzy BWM and hybrid methodologies for industrial robot selection. Fuzzy extensions of BWM are proposed using hesitant and GITrF multiplicative preference relations. The linguistic terms are used to express the reference comparisons of the best criterion and the worst criterion. These linguistic terms are expressed in hesitant fuzzy elements and GITrF numbers, respectively. The non-linear constrained mathematical models are constructed to obtain the hesitant and GITrF weights of criteria that are converted to crisp weights. The consistency ratio of both extensions is proposed to check the reliability of the methods. The results of comparative case analysis show the advantage and suitability of the proposed methods due to higher comparison consistency as compared to BWM and fuzzy BWM. For different applications, there are different robots having capabilities and specifications accordingly. For a particular application and industrial requirement, proper and suitable selection of a robot is a difficult task. Numerous robot selection methods are available. Considering the research works on industrial robot selection, three Multiple Criteria Decision Making (MCDM) methodologies are proposed. (1) Group BWM is employed for the proper selection of robots. Weighing the decision-makers by considering their past experience is an important factor considered for expert and reliable selection of robots. Objective weights to describe the importance of the attributes along with the decision-makers’ subjective preferences to describe the weights of the attribute are considered. (2) A hybrid MCDM methodology is proposed by integrating BWM with the evaluation based on distance from average solution method. (3) GITrF best-worst method is integrated with extended Technique for Order of Preference by Similarity to Ideal Solution and extended VlseKriterijumska Optimizacija I Kompromisno Resenje methods for the selection of the optimal industrial robot using fuzzy information. 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. Comparative studies and sensitivity analysis are performed to check the stability and reliability of the proposed methodologies. The proposed hybrid and fuzzy methodologies are not limited to robot selection; instead, they are general and can be used for any criteria-based selection problems.