Title A GREY COMBINED COMPROMISE SOLUTION (COCOSO-G) METHOD FOR SUPPLIER SELECTION IN CONSTRUCTION MANAGEMENT
Authors YAZDANI, MORTEZA, Wen, Zhi , Liao, Huchang , Banaitis, Audrius , Turskis, Zenonas
External publication No
Means J. Civ. Eng. Manage.
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 2
JCR Impact 2.338
SJR Impact 0.543
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076269525&doi=10.3846%2fjcem.2019.11309&partnerID=40&md5=22a7936d0309b3cde91ddeda17d0e82b
Publication date 01/01/2019
ISI 000507396100011
Scopus Id 2-s2.0-85076269525
DOI 10.3846/jcem.2019.11309
Abstract This study investigates an extended version of the combined compromise\n solution method with grey numbers, named CoCoSo-G for short, to measure\n the performance of suppliers in a construction company in Madrid. Seven\n criteria from a relevant previous study are the basis for assessing the\n performance of suppliers, while ten suppliers are composing our decision\n matrix. To initiate the decision-making process, we invite experts to\n aid us in the qualitative evaluation of the suppliers using grey\n interval values. Two weighting methods, including the DEMATEL (Decision\n Making Trial and Evaluation Laboratory) and BWM (best worst method) are\n used to achieve the importance of supplier criteria in a combined\n manner. The DEMATEL method is used to realise the best and worst\n criteria, and the BWM is used to sort the criteria according to a linear\n programming formulation. The CoCoSo-G method used to release the score\n of each supplier and rank them. We compare the results obtained by the\n CoCoSo-G with those obtained by the Complex Proportional Assessment\n method. It is evident that offering grey values for supplier\n qualification, using the combined weighting tool and proposing the new\n CoCoSo-G approach facilitate the evaluation process while indicating\n trustable outcomes.
Keywords multi-criteria decision-making; supplier selection; grey values; Combined Compromise Solution method; Co-CoSo; CoCoSo-G; Best-Worst method
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