Dynamic multicriteria group decision-making method with automatic reliability and weight calculation

• Published in: Information sciences 2023-07, Vol.634, p.400-422
• Main Authors: Du, Yuan-Wei, Zhong, Jiao-Jiao
• Format: Article
• Language: English
• Subjects: Consensus reaching; Evidence distance; Informational entropy; Multicriteria group decision-making; Weight and reliability
• ISSN: 0020-0255; 1872-6291
• DOI: 10.1016/j.ins.2023.03.092

•Multicriteria group decision-making (MCGDM) is performed dynamically.•Dynamic MCGDM method with automatic reliability and weight is proposed.•The method of automatically determining reliability is constructed based on evidence distance.•The method of automatically determining weight is constructed based on Deng entropy.•Generalized combination rule is used to solve MCGDM problem with two parameters. With the increasing complexity of socioeconomic environments, multicriteria group decision-making (MCGDM) has attracted increasing attention from researchers. Experts’ weight and reliability are crucial to MCGDM and have an important influence on decision-making accuracy. In reality, an expert’s weight and reliability might vary with the influence of factors such as changes in expert psychology and the collection of additional information. Thus, this study proposes a dynamic MCGDM method with automatic reliability and weight calculation. First, we introduce a generalized combination rule into MCGDM and propose methods for automatically determining experts’ weight and reliability by mining evidence. Here, experts’ weight can be calculated according to the entropy of evidence, while experts’ reliability can be calculated according to evidence distance from the perspectives of horizontal comparison and longitudinal comparison. Then, the consensus-reaching process is taken into account in MCGDM; experts are allowed to modify and change their judgments, and experts’ weight and reliability can be automatically updated in each round of interaction. Finally, we provide an illustrative example and make some comparisons to demonstrate the applicability and advantages of the proposed method.