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A dynamic group MCDM model with intuitionistic fuzzy set: perspective of alternative queuing method. (English) Zbl 1486.91031

Summary: Dynamic multi-criteria decision making (DMCDM) is prevalent in real life, where the evaluations are given sequentially across time and earlier evaluations will influence later ones. Moreover, alternatives and criteria are allowed to vary with time. However, on the one hand, such dynamic change is rarely considered under the situation of group decision making. On the other hand, recent DMCDM methods just aggregate the evaluations from different periods, which can not accurately reflect the relative relation between alternatives due to constant change of alternatives and criteria. Motivated by these cases, we provide an insight with alternative queuing method (AQM) and intuitionistic fuzzy set (IFS) into dynamic group MCDM (DGMCDM), which ranks the alternatives based on preference relation. In the proposed model, we generate current weights of decision makers (DMs) by introducing induced ordered weighted averaging (IOWA) operator which acts as a link among the weights collected across time. Moreover, we extend classical AQM by using fuzzy preference relation (FPR) instead of 0-1 preference relationship in paired comparison between alternatives. Additionally, a feedback mechanism is defined within the framework of extended AQM, where later FPRs will be influenced by the earlier ones as well as carried to the next period. Our method is of great effectiveness and flexibility with complicated and changeable environment, which has been demonstrated in the field of supplier selection undergoing three periods. Furthermore, we make a comparative analysis of the method with classical AQM and static MCDM.

MSC:

91B06 Decision theory
90B50 Management decision making, including multiple objectives
03E72 Theory of fuzzy sets, etc.
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