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Contractor selection in MCDM context using fuzzy AHP | ||
Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies) | ||
مقاله 7، دوره 7، شماره 1، فروردین 2014، صفحه 151-173 اصل مقاله (526.46 K) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22059/ijms.2014.36206 | ||
نویسندگان | ||
Rahmatollah Gholipour1؛ Gholamreza Jandaghi2؛ Reza Rajaei* 3 | ||
1Associate Professor, Faculty of Management, University of Tehran, Iran | ||
2Professor, Faculty of Management Farabi Campus, University of Tehran, Iran | ||
3PHD candidate of financial management, Pardis Farabi college, university of Tehran, Iran | ||
چکیده | ||
Contractor selection is one of the most important problem in supply chain and its strongly effect on firm`s performance. Because a significant amount of a university`s budget assigns to construction contracts, contractor selection is an important problem for the financial status of universities. Since Contractor selection is a multi-criteria decision making problem (MCDM), lots of methods proposed to face this problem. Selection is a broad comparison of contractors using a common set of criteria and measures. Analytic hierarchy process (AHP) and other traditional methods widely used for contractor and vendor selection by researches regarding to lots linguistic variables and both qualitative and quantitative criteria and to tackle ambiguous nature of contractor selection problem, although there is some Insufficiency about them. In this article we use FAHP that is a fuzzy extension of AHP to handle the fuzziness of the data involved in deciding the preferences of different decision variables. The linguistic level of comparisons produced by experts for each comparison is tapped in the form triangular fuzzy numbers to construct fuzzy pairwise comparison matrices. We priorities Tehran university`s construction contractor about each criteria and determine the best one about all of them. | ||
کلیدواژهها | ||
Analytic Hierarchy Process؛ Contractor selection؛ fuzzy set theory؛ multi-criteria decision making problem | ||
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