TY - JOUR
T1 - A hybrid neutrosophic group ANP-TOPSIS framework for supplier selection problems
AU - Abdel-Basset, Mohamed
AU - Mohamed, Mai
AU - Smarandache, Florentin
N1 - Publisher Copyright:
© 2018 by the authors.
Funding Information:
This work was financed by the European Community (ENV4-CT98-0798) and the Swiss federal office for education and science (BBW, grant 98.0090).
Publisher Copyright:
© 2018 by the authors.
PY - 2018/6/15
Y1 - 2018/6/15
N2 - One of the most significant competitive strategies for organizations is sustainable supply chain management (SSCM). The vital part in the administration of a sustainable supply chain is the sustainable supplier selection, which is a multi-criteria decision-making issue, including many conflicting criteria. The valuation and selection of sustainable suppliers are difficult problems due to vague, inconsistent and imprecise knowledge of decision makers. In the literature on supply chain management for measuring green performance, the requirement for methodological analysis of how sustainable variables affect each other, and how to consider vague, imprecise and inconsistent knowledge, is still unresolved. This research provides an incorporated multi-criteria decision-making procedure for sustainable supplier selection problems (SSSPs). An integrated framework is presented via interval-valued neutrosophic sets to deal with vague, imprecise and inconsistent information that exists usually in real world. The analytic network process (ANP) is employed to calculate weights of selected criteria by considering their interdependencies. For ranking alternatives and avoiding additional comparisons of analytic network processes, the technique for order preference by similarity to ideal solution (TOPSIS) is used. The proposed framework is turned to account for analyzing and selecting the optimal supplier. An actual case study of a dairy company in Egypt is examined within the proposed framework. Comparison with other existing methods is implemented to confirm the effectiveness and efficiency of the proposed approach.
AB - One of the most significant competitive strategies for organizations is sustainable supply chain management (SSCM). The vital part in the administration of a sustainable supply chain is the sustainable supplier selection, which is a multi-criteria decision-making issue, including many conflicting criteria. The valuation and selection of sustainable suppliers are difficult problems due to vague, inconsistent and imprecise knowledge of decision makers. In the literature on supply chain management for measuring green performance, the requirement for methodological analysis of how sustainable variables affect each other, and how to consider vague, imprecise and inconsistent knowledge, is still unresolved. This research provides an incorporated multi-criteria decision-making procedure for sustainable supplier selection problems (SSSPs). An integrated framework is presented via interval-valued neutrosophic sets to deal with vague, imprecise and inconsistent information that exists usually in real world. The analytic network process (ANP) is employed to calculate weights of selected criteria by considering their interdependencies. For ranking alternatives and avoiding additional comparisons of analytic network processes, the technique for order preference by similarity to ideal solution (TOPSIS) is used. The proposed framework is turned to account for analyzing and selecting the optimal supplier. An actual case study of a dairy company in Egypt is examined within the proposed framework. Comparison with other existing methods is implemented to confirm the effectiveness and efficiency of the proposed approach.
KW - Analytic network process
KW - Interdependency of criteria
KW - Neutrosophic set
KW - Sustainable supplier selection problems (SSSPs)
KW - TOPSIS
UR - http://www.scopus.com/inward/record.url?scp=85048886188&partnerID=8YFLogxK
U2 - 10.3390/sym10060226
DO - 10.3390/sym10060226
M3 - Article
AN - SCOPUS:85048886188
SN - 2073-8994
VL - 10
SP - 1
EP - 22
JO - Symmetry
JF - Symmetry
IS - 6
M1 - 226
ER -