Affiliations: [a] School of Economy and Management, Harbin Engineering University, Harbin, China
| [b] School of Economics and Management, Beijing University of Technology, Beijing, China
| [c] Department Economics, McMaster University, Hamilton, ON, Canada
Correspondence:
[*]
Corresponding author. Jinqiu Li, School of Economy and Management, Harbin Engineering University, Harbin 150001, China. E-mail: hanying911@126.com.
Abstract: For multi-attribute decision-making (MADM) problems with temporal characteristics and attribute values of interval-valued intuitionistic normal fuzzy numbers, dynamic interval-valued intuitionistic normal fuzzy weighted averaging (DIINFWA) operators are presented, and their properties are proved. Since attribute weights and time weights have both been unknown in MADM problems, we propose a dynamic interval-valued intuitionistic normal fuzzy MADM method. In this method, a combination weighting method of gray correlation analysis and the maximum deviation method are used to solve for attribute weights, comprehensively considering the subjective experience of decision-makers and objectives of decision data; time weights are decomposed into time-constant and time-variable weight vectors. We determine time weights using the time function, combining information entropy and a logistic function. According to the algorithm of interval-valued intuitionistic normal fuzzy numbers, decision-making information in different time sequences are aggregated using the proposed DIINFWA operators. We construct a dynamic interval-valued intuitionistic normal fuzzy comprehensive decision matrix and use the VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje) method to obtain the optimal solution. Finally, the feasibility and significance of the presented method compared to existing methods are verified through analysis of numerical examples.
