A hesitant fuzzy linguistic Choquet integral-based MULTIMOORA method for multiple criteria decision making and its application in talent selection
Data
2019Autorius
Liao, Zhiqiang
Liao, Huchang
Gou, Xunjie
Xu, Zeshui
Zavadskas, Edmundas Kazimieras
Metaduomenys
Rodyti detalų aprašąSantrauka
In qualitative multiple criteria decision making (MCDM) process, dealing with complex linguistic evaluations and modeling interaction phenomena among criteria are two important issues. The purpose of this study is to introduce two Choquet integral operators for HFLTSs to tackle interactions among criteria and then implement these operators to a well-known MCDM method, namely, the MULTIMOORA(multi-objective optimization by ratio analysis plus the full multiplicative form). Firstly, we introduce new operations for HFLTSs based on some linguistic scale functions. Then, we define two hesitant fuzzy linguistic Choquet integral operators and propose a novel score function for hesitant fuzzy linguistic elements. Afterwards, we improve the HFL-MULTIMOORA method to handle the hesitant fuzzy linguistic MCDM problems in which the criteria are inter-dependent. Finally, an illustration regarding the human resource development at Sichuan University is shown to verify the applicability and validity of the proposed method.