A Method for Multicriteria Group Decision Making with Different Evaluation Criterion Sets

• Published in: Mathematical problems in engineering Vol. 2018; no. 2018; pp. 1 - 10
• Main Authors: You, Tian-Hui, Liu, Yang, Li, Ming-Yang, Fan, Zhi-Ping
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018; Hindawi; Hindawi Limited
• Subjects: Applied mathematics; Decision making; Decision making models; Decision support systems; Mathematical analysis; Mathematical models; Matrix methods; Multiple criterion; Normalizing; Ranking; Sentiment analysis; Weight
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2018/7189451

Multicriteria group decision making (MCGDM) with different evaluation criterion sets is a special kind of MCGDM problem, where criterion sets considered by multiple experts may be different, while research concerning this issue is still relatively scarce. The objective of this paper is to develop a method for MCGDM with different evaluation criterion sets. In the method, according to different criterion sets, several criterion subsets are first constructed, where each criterion subset includes the criteria concerned by the same group of experts. Then, with respect to each criterion subset, a ranking of alternatives is determined by normalizing the decision matrix and calculating the ranking value of each alternative with respect to the criterion subset. Next, according to the ranking of alternatives with respect to each criterion subset, a ranking possibility matrix of alternatives with respect to the criterion subset is constructed. Further, the weight of each criterion subset is determined according to weights of the experts and weights of the criteria in the criterion subset. Moreover, an overall ranking possibility matrix is constructed by aggregating the ranking possibility matrices and weights concerning different criterion subsets, and the final ranking result of alternatives is determined by solving a linear assignment model, where the elements in the overall ranking possibility matrix are regarded as the benefits on assigning each alternative into different ranking positions. Finally, a numerical example is given to illustrate the use of the proposed method.