Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/4747
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dc.contributorSeyed Mohammad Hashemian-
dc.contributorMajid Behzadian-
dc.contributorReza Samizadeh-
dc.contributorJoshua Ignatius-
dc.date.accessioned2023-05-05T06:49:56Z-
dc.date.available2023-05-05T06:49:56Z-
dc.date.issued2014en_US
dc.identifier.otherDOI 10.1007/s00170-014-5843-2-
dc.identifier.urihttp://localhost/handle/Hannan/4747-
dc.description.abstractThe quality and delivery performance of a typical company depends largely on the capability of its suppliers. It is therefore important for a company to evaluate the performance of its existing suppliers. However, the problem of supplier evaluation is rather complex when a group of decision makers responsible for these suppliers are geographically dispersed. Evaluating decisions requiring the elicitation of vague and imprecise linguistic information expressed in fuzzy terms. For this purpose, a hybrid fuzzy group decision-making approach for supplier evaluation is proposed, integrating the fuzzy analytic hierarchy process (F-AHP) and the fuzzy preference-ranking-organization-method-for-enrichment-ofevaluation (PROMETHEE) group decision support system (F-PROMETHEE GDSS) method. F-AHP is used to determine the weight of multiple criteria while F-PROMETHEE GDSS is applied for the final ranking of suppliers from a group decision viewpoint. The approach advances the supplier evaluation context in two aspects. First, it treats each decision maker uniquely in terms of the preference function and threshold levels. Second, it provides rapid communication between teams through video conferencing. The hybrid approach is used to evaluate the suppliers of a dairy company.en_US
dc.language.isoen_USen_US
dc.subjectSupplier evaluation . Fuzzy AHP . Fuzzy PROMETHEE GDSSen_US
dc.titleA fuzzy hybrid group decision support system approach for the supplier evaluation process-
dc.typeArticleen_US
Appears in Collections:تمامی گرایش های مدیریت شامل مدیریت بازرگانی و صنعتی

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Full metadata record
DC FieldValueLanguage
dc.contributorSeyed Mohammad Hashemian-
dc.contributorMajid Behzadian-
dc.contributorReza Samizadeh-
dc.contributorJoshua Ignatius-
dc.date.accessioned2023-05-05T06:49:56Z-
dc.date.available2023-05-05T06:49:56Z-
dc.date.issued2014en_US
dc.identifier.otherDOI 10.1007/s00170-014-5843-2-
dc.identifier.urihttp://localhost/handle/Hannan/4747-
dc.description.abstractThe quality and delivery performance of a typical company depends largely on the capability of its suppliers. It is therefore important for a company to evaluate the performance of its existing suppliers. However, the problem of supplier evaluation is rather complex when a group of decision makers responsible for these suppliers are geographically dispersed. Evaluating decisions requiring the elicitation of vague and imprecise linguistic information expressed in fuzzy terms. For this purpose, a hybrid fuzzy group decision-making approach for supplier evaluation is proposed, integrating the fuzzy analytic hierarchy process (F-AHP) and the fuzzy preference-ranking-organization-method-for-enrichment-ofevaluation (PROMETHEE) group decision support system (F-PROMETHEE GDSS) method. F-AHP is used to determine the weight of multiple criteria while F-PROMETHEE GDSS is applied for the final ranking of suppliers from a group decision viewpoint. The approach advances the supplier evaluation context in two aspects. First, it treats each decision maker uniquely in terms of the preference function and threshold levels. Second, it provides rapid communication between teams through video conferencing. The hybrid approach is used to evaluate the suppliers of a dairy company.en_US
dc.language.isoen_USen_US
dc.subjectSupplier evaluation . Fuzzy AHP . Fuzzy PROMETHEE GDSSen_US
dc.titleA fuzzy hybrid group decision support system approach for the supplier evaluation process-
dc.typeArticleen_US
Appears in Collections:تمامی گرایش های مدیریت شامل مدیریت بازرگانی و صنعتی

Files in This Item:
File Description SizeFormat 
188.pdf498.52 kBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributorSeyed Mohammad Hashemian-
dc.contributorMajid Behzadian-
dc.contributorReza Samizadeh-
dc.contributorJoshua Ignatius-
dc.date.accessioned2023-05-05T06:49:56Z-
dc.date.available2023-05-05T06:49:56Z-
dc.date.issued2014en_US
dc.identifier.otherDOI 10.1007/s00170-014-5843-2-
dc.identifier.urihttp://localhost/handle/Hannan/4747-
dc.description.abstractThe quality and delivery performance of a typical company depends largely on the capability of its suppliers. It is therefore important for a company to evaluate the performance of its existing suppliers. However, the problem of supplier evaluation is rather complex when a group of decision makers responsible for these suppliers are geographically dispersed. Evaluating decisions requiring the elicitation of vague and imprecise linguistic information expressed in fuzzy terms. For this purpose, a hybrid fuzzy group decision-making approach for supplier evaluation is proposed, integrating the fuzzy analytic hierarchy process (F-AHP) and the fuzzy preference-ranking-organization-method-for-enrichment-ofevaluation (PROMETHEE) group decision support system (F-PROMETHEE GDSS) method. F-AHP is used to determine the weight of multiple criteria while F-PROMETHEE GDSS is applied for the final ranking of suppliers from a group decision viewpoint. The approach advances the supplier evaluation context in two aspects. First, it treats each decision maker uniquely in terms of the preference function and threshold levels. Second, it provides rapid communication between teams through video conferencing. The hybrid approach is used to evaluate the suppliers of a dairy company.en_US
dc.language.isoen_USen_US
dc.subjectSupplier evaluation . Fuzzy AHP . Fuzzy PROMETHEE GDSSen_US
dc.titleA fuzzy hybrid group decision support system approach for the supplier evaluation process-
dc.typeArticleen_US
Appears in Collections:تمامی گرایش های مدیریت شامل مدیریت بازرگانی و صنعتی

Files in This Item:
File Description SizeFormat 
188.pdf498.52 kBAdobe PDFThumbnail
Preview File