Author
Zhong-xing Wang
Bio: Zhong-xing Wang is an academic researcher. The author has co-authored 1 publications.
Papers
More filters
02 Aug 2021
TL;DR: Decision-making models based on decision makers’ satisfaction degree with IHFPR are developed, and an illustrative example in conjunction with comparative analysis is used to demonstrate the proposed models are feasible and efficiency for practical MCDM problems.
Abstract:
To address the situation where the incomplete hesitant fuzzy preference relation (IHFPR) is necessary, this paper develops decision-making models based on decision makers’ satisfaction degree with IHFPR. First, the consistency measures from the perspectives of additive and multiplicative consistent IHFPR are defined based on the relationships between the IHPFRs and their corresponding priority weight vector, respectively. Second, two decision-making models are developed in view of the proposed additive and multiplicative consistency measures. The main characteristic of the constructed model sarethey taking into account the decision makers’ satisfaction degree. The objective functions of the models are developed by maximizing the parameter of satisfaction degree. Third, a square programming model is developed to obtain the decision makers’ weights byutilizing the optimal priority weight vectors information, the solution of the model is obtained by solving the partial derivatives ofLagrange function.Finally, a procedure for multi-criteria decision-making (MCDM) problems with IHFPRs is given, and an illustrative example in conjunction with comparative analysis is used to demonstrate the proposed models are feasible and efficiency for practical MCDM problems.
3 citations
Cited by
More filters
TL;DR: In this paper , the authors proposed a multistage decision-making framework considering quantum-guided expert transition based on normal cloud models, and the feasibility and applicability of the proposed method are illustrated via a power grid emergency evaluation example by conducting analyses and comparisons of the decision results.
6 citations
TL;DR: The authors presented the fuzzy incomplete linguistic preference relations (Fuzzy InLinPreRa) approach as evaluated by decision-makers dealing with increasing complexity and uncertain economics, as well as social and managerial problems.
Abstract: The effectiveness of preference relations in modeling decision-making processes makes it one of the most common representations of information use for solving decision-making problems. This research presents the fuzzy incomplete linguistic preference relations (Fuzzy InLinPreRa) approach as evaluated by decision-makers dealing with increasing complexity and uncertain economics, as well as social and managerial problems. By using Fuzzy InLinPreRa, the consistency measurements of decision-makers’ evaluations will provide more accurate and reasonable solutions, allowing decision-makers to consider the objective weights of both the criteria and experts. An empirical example of the measurement of brand personality is included herein to demonstrate the feasibility of this method.