An integrated model-based interactive approach to FMAGDM with incomplete preference information |
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Authors: | Zeshui Xu |
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Institution: | (1) Department of Management Science and Engineering, Northeastern University, Shenyang, China;(2) Department of Economics, School of Business Administration, Northeastern University, 110004 Shenyang, China; |
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Abstract: | Incomplete fuzzy preference relations, incomplete multiplicative preference relations, and incomplete linguistic preference
relations are very useful to express decision makers’ incomplete preferences over attributes or alternatives in the process
of decision making under fuzzy environments. The aim of this paper is to investigate fuzzy multiple attribute group decision
making problems where the attribute values are represented in intuitionistic fuzzy numbers and the information on attribute
weights is provided by decision makers by means of one or some of the different preference structures, including weak ranking,
strict ranking, difference ranking, multiple ranking, interval numbers, incomplete fuzzy preference relations, incomplete
multiplicative preference relations, and incomplete linguistic preference relations. We transform all individual intuitionistic
fuzzy decision matrices into the interval decision matrices and construct their expected decision matrices, and then aggregate
all these expected decision matrices into a collective one. We establish an integrated model by unifying the collective decision
matrix and all the given different structures of incomplete weight preference information, and develop an integrated model-based
approach to interacting with the decision makers so as to adjust all the inconsistent incomplete fuzzy preference relations,
inconsistent incomplete linguistic preference relations and inconsistent incomplete multiplicative preference relations into
the ones with acceptable consistency. The developed approach can derive the attribute weights and the ranking of the alternatives
directly from the integrated model, and thus it has the following prominent characteristics: (1) it does not need to construct
the complete fuzzy preference relations, complete linguistic preference relations and complete multiplicative preference relations
from the incomplete fuzzy preference relations, incomplete linguistic preference relations and incomplete multiplicative preference
relations, respectively; (2) it does not need to unify the different structures of incomplete preferences, and thus can simplify
the calculation and avoid distorting the given preference information; and (3) it can sufficiently reflect and adjust the
subjective desirability of decision makers in the process of interaction. A practical example is also provided to illustrate
the developed approach. |
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