Journal
COMPUTERS & INDUSTRIAL ENGINEERING
Volume 110, Issue -, Pages 138-150Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2017.05.033
Keywords
Multi-criteria group decision making; Intuitionistic fuzzy preference relation; Best-worst method; Consistency; Healthcare appointment registration system
Funding
- National Natural Science Foundation of China [71571123, 71501135, 71532007, 11671001, 61472056]
- Scientific Research Foundation for Excellent Young Scholars at Sichuan University [2016SCU04A23]
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Intuitionistic fuzzy preference relation (IFPR) is an efficient tool in tackling comprehensive multi-criteria group decision making (MCGDM) problems via pairwise comparisons. Based on the intuitionistic fuzzy analytic hierarchy process (IFAHP) and the best-worst method (BWM), this paper aims to put forward a novel graph-based group decision making approach called the intuitionistic fuzzy best-worst method (IF-BWM) for MCGDM. To achieve this goal, we first aggregate the individual IFPRs provided by the decision makers into a collective IFPR by the intuitionistic fuzzy weighted averaging (IFWA) operator. Afterwards, we draw the directed network according to the collective IFPR, and then design an algorithm to identify the best and worst criteria through computing the out-degrees and in-degrees of the directed network. Furthermore, to derive the weights of criteria, some mathematical models corresponding to the different definitions of consistent IFPR are developed. Finally, the procedure of the IF-BWM is proposed for practical applications and three numerical examples are given to illustrate the approach. (C) 2017 Published by Elsevier Ltd.
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