A Dynamic Programming Algorithm Based Clustering Model and Its Application to Interval Type-2 Fuzzy Large-Scale Group Decision-Making Problem

This article focuses on employing the dynamic programming algorithm to solve the large-scale group decision-making problems, where the preference information takes the form of linguistic variables. Specifically, considering the linguistic variables cannot be directly computed, the interval type-2 fu...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems Vol. 30; no. 1; pp. 108 - 120
Main Authors: Pan, Xiaohong, Wang, Yingming, He, Shifan, Chin, Kwai-Sang
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Centroid-based ranking method
Centroids
Clustering
Clustering algorithms
Clustering methods
Decision making
Dynamic programming
dynamic programming algorithm-based clustering model
Fuzzy sets
Heuristic algorithms
interval type-2 fuzzy sets
large-scale group decision-making (GDM)
Linguistics
ISSN:1063-6706, 1941-0034
Online Access:Get full text
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Summary:This article focuses on employing the dynamic programming algorithm to solve the large-scale group decision-making problems, where the preference information takes the form of linguistic variables. Specifically, considering the linguistic variables cannot be directly computed, the interval type-2 fuzzy sets are employed to encode them. Then, new distance model and similarity model are respectively developed to measure the relationships between the interval type-2 fuzzy sets. After that, a dynamic programming algorithm-based clustering model is proposed to cluster the decision-makers from the overall perspective. Moreover, by taking both the cluster center and the group size into consideration, a new model is introduced to determine the weights of clusters and decision-makers, respectively. Finally, a centroid-based ranking method is developed to compare and rank the alternatives, and two illustrative experiments are provided to illustrate the effectiveness of the proposed method. Comparisons and discussions are also conducted to verify its superiority.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2020.3032794