Title :
TOPSIS-Based Nonlinear-Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets
Author_Institution :
Sch. of Manage., Fuzhou Univ., Fuzhou, China
fDate :
4/1/2010 12:00:00 AM
Abstract :
Interval-valued intuitionistic fuzzy (IVIF) sets are useful to deal with fuzziness inherent in decision data and decision-making processes. The aim of this paper is to develop a nonlinear-programming methodology that is based on the technique for order preference by similarity to ideal solution to solve multiattribute decision-making (MADM) problems with both ratings of alternatives on attributes and weights of attributes expressed with IVIF sets. In this methodology, nonlinear-programming models are constructed on the basis of the concepts of the relative-closeness coefficient and the weighted-Euclidean distance. Simpler auxiliary nonlinear-programming models are further deduced to calculate relative-closeness of IF sets of alternatives to the IVIF-positive ideal solution, which can be used to generate the ranking order of alternatives. The proposed methodology is validated and compared with other similar methods. A real example is examined to demonstrate the applicability and validity of the methodology proposed in this paper.
Keywords :
decision making; fuzzy set theory; nonlinear programming; TOPSIS-based nonlinear-programming methodology; decision-making processes; interval-valued intuitionistic fuzzy sets; multiattribute decision making; weighted-Euclidean distance; Interval-valued intuitionistic fuzzy (IVIF) set; mathematical programming; multiattribute decision-making (MADM); technique for order preference by similarity to ideal solution (TOPSIS); uncertainty;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2010.2041009