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A heterogeneous picture fuzzy SWARA-MARCOS evaluation framework based on a novel cross-entropy measure.

Authors :
Peng, Juan Juan
Chen, Xin Ge
Tan, Hao
Sun, Jing Yi
Long, Qing Qi
Jiang, Luo Luo
Source :
International Journal of Systems Science; Jun2024, Vol. 55 Issue 8, p1528-1552, 25p
Publication Year :
2024

Abstract

Multi-criteria decision-making (MCDM) entails a heterogeneous decision-making problem, which poses challenges for decision-makers (DMs) in generating an optimal solution. To address this, we have proposed a heterogeneous evaluation framework. First, a novel picture fuzzy cross-entropy measure was defined with the simultaneous consideration of uncertainty and hesitancy of picture fuzzy information, overcoming the shortcomings of the existing cross-entropy measure in relation to its validity and properties. Next, an optimisation-model for determining the objective weights of criteria was constructed based on the proposed closeness measurement and the step-wise weight assessment ratio analysis (SWARA) method. This model was constituted from both objective and subjective perspectives under the circumstance of completely unknown criterion information. Additionally, the conventional Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was extended to the picture fuzzy environment, and a normalisation method was developed to transform heterogeneous judgments, including linguistic terms, interval numbers, and picture fuzzy numbers, into a unified representation form. A heterogeneous picture fuzzy SWARA-MARCOS evaluation framework was then established and used to solve a military equipment supplier selection problem. The results demonstrated the validity and feasibility of the proposed evaluation framework, while sensitivity, comparative, and complexity analyses demonstrated the robustness and superiority of it. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207721
Volume :
55
Issue :
8
Database :
Complementary Index
Journal :
International Journal of Systems Science
Publication Type :
Academic Journal
Accession number :
177179279
Full Text :
https://doi.org/10.1080/00207721.2024.2312881