Abstract
Bodies' behaviors remain important to the decision-making process of two-sided matching. The two-sided matching problem under interval-valued intuitionistic fuzzy environment is investigated from the perspective of bodies' behavior, i.e., the behavior of matching willingness. For solving the problem, a normalized interval-valued score function is firstly presented. Through using this function, interval-valued intuitionistic fuzzy number (IvIFN) preference matrices are converted to normalized interval-valued score matrices. The normalized interval-valued score matrices are then converted to score matrices. Based on score matrices, the matching willingness can be obtained by solving an optimal model. Based on score matrices and matching willingness matrix, the weighting score matrices are set up. Aiming at weighting score matrices, we use the TOPSIS method to calculate the closeness degrees. Based on closeness degree matrices and matching matrix, a two-sided matching (TsM) model is developed. Considering the same or different statuses of bodies, the TsM model is transformed to the one-goal TsM model. Through model solution, the optimal scheme of TsM can be obtained. Ultimately, the availability of TOPSIS based TsM method is illustrated by using a matching example of virtual reality technology.
Highlights
Two-sided matching (TsM) is a well-known research direction of decision-making
This paper extended the application scope of Interval-valued intuitionistic fuzzy sets (IVIFSs) to TsM field, and studied the TsM problem from bodies’ behaviors using a matching example of virtual reality technology
The interval-valued intuitionistic fuzzy number (IvIFN) matrix is converted into normalized interval-valued score matrices, and into score matrices
Summary
Two-sided matching (TsM) is a well-known research direction of decision-making. In decision-making process, owing to the increasing complexity of the society and economy, inadequacy of human knowledge and imprecise of judgement, the decision-makers or bodies may give their preferences using intuitionistic fuzzy sets (IFSs) rather than some exact values, such ordinal numbers, order relations, or linguistic variables [18]. A new interval-valued knowledge measure for the IvIFSs is presented firstly, and it was applied into decision making problems in order to demonstrate it is simpler and more attractive in comparison with other existing measures [28]. It is known that bodies’ behaviors play an important role in TsM process For this reason, this paper extended the application scope of IVIFSs to TsM field, and studied the TsM problem from bodies’ behaviors using a matching example of virtual reality technology
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