Journal
KNOWLEDGE-BASED SYSTEMS
Volume 67, Issue -, Pages 71-89Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2014.06.006
Keywords
Outsourcing provider; Multiattribute group decision making; Production operation; Fuzzy linear programming; Supply chain management
Categories
Funding
- Key Program of National Natural Science Foundation of China [71231003]
- National Natural Science Foundation of China [71061006, 61263018, 71171055, 71001015]
- Program for New Century Excellent Talents in University (the Ministry of Education of China) [NCET-10-0020]
- Specialized Research Fund for the Doctoral Program of Higher Education of China [20113514110009]
- Humanities Social Science Programming Project of Ministry of Education of China [09YGC630107]
- Natural Science Foundation of Jiangxi Province of China [20114BAB201012]
- Science and Technology Project of Jiangxi Province Educational Department of China [GJJ12265, GJJ12740]
- Twelve five Programming Project of Jiangxi Province Social Science [13GL17]
- Excellent Young Academic Talent Support Program of Jiangxi University of Finance and Economics
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Considering various situations and characteristics of supply chain management, we regard the outsourcing provider selection as a type of fuzzy inhomogenous multiattribute group decision making (MAGDM) problems with fuzzy alternatives' comparisons and incomplete weight information. Hereby we focus on developing a new fuzzy linear programming method for solving such MAGDM problems. In this method, the decision makers' preferences are given through pair-wise alternatives' comparisons with fuzzy truth degrees represented as trapezoidal fuzzy numbers (TrFNs). Intuitionistic fuzzy sets, TrFNs, intervals and real numbers are used to express the inhomogenous decision information. Under the condition that the fuzzy positive ideal solution (PIS) and fuzzy negative ideal solution (NIS) are known, the fuzzy consistency and inconsistency indices are defined on the basis of the relative closeness degrees and expressed with TrFNs. The attribute weights are estimated through constructing a new fuzzy linear programming model, which is solved by the developed method of fuzzy linear programming with TrFNs. Through solving the constructed linear goal programming model, we obtain the collective comprehensive relative closeness degrees of alternatives to the fuzzy PIS, which are used to rank the alternatives. The effectiveness of the proposed method is verified with an example of IT outsourcing provider selection. (C) 2014 Elsevier B.V. All rights reserved.
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