Indexed by:
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.
Keyword:
Reprint Author's Address:
Email:
Source :
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
ISSN: 1064-1246
Year: 2018
Issue: 4
Volume: 35
Page: 3937-3954
2 . 0 0 0
JCR@2022
ESI Discipline: COMPUTER SCIENCE;
ESI HC Threshold:161
JCR Journal Grade:3
Cited Count:
WoS CC Cited Count: 5
SCOPUS Cited Count: 6
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 11
Affiliated Colleges: