Supplier Evaluation Considering Green Production Based on Probabilistic Linguistic Information

The evaluation of manufacturing component suppliers is focused on economic indicators, with insufficient emphasis on green indicators and no consideration of the correlation between indicators. Firstly, indicators related to green production are incorporated into the supplier evaluation system. Then...

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Bibliographic Details
Published in:Energies (Basel) 2022-10, Vol.15 (19), p.7420
Main Authors: Yuan, Shuailei, Liu, Aijun, Li, Zengxian, Yang, Yun, Liu, Jing, Su, Yue
Format: Article
Language:English
Subjects:
Decision making
Economic indicators
Environmental impact
Environmental protection
Evaluation
Fuzzy sets
greener production
Indicators
Linguistics
Literature reviews
Manufacturing
manufacturing industry
multi-attribute decision making
Performance management
probabilistic linguistic weighted partitioned Maclaurin symmetric mean operator (PLWPMSM)
Product life cycle
Product quality
Production methods
Stock exchanges
supplier evaluation
Suppliers
Supply chains
Vendor relations
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Summary:The evaluation of manufacturing component suppliers is focused on economic indicators, with insufficient emphasis on green indicators and no consideration of the correlation between indicators. Firstly, indicators related to green production are incorporated into the supplier evaluation system. Then, for the problem that attributes in decision making can be divided into different categories and there are interrelationships between attributes of the same category, a multi-attribute decision-making (MADM) method based on the partitioned Maclaurin symmetric mean operator (PMSM) is proposed. Finally, the proposed MADM method was applied to the evaluation of component suppliers considering green production. Comparing popular decision methods with the newly proposed method for validation, it was demonstrated that the proposed multi-attribute decision method is highly flexible and versatile. Furthermore, the newly proposed aggregation operator can not only handle the correlation between multiple attributes, but also be converted to other general aggregation operators through parameter adjustment.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15197420