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An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information

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Abstract

This study aims to introduce a series of novel distance measures of an intuitionistic fuzzy set and an extended Multi-attributive Border Approximation Area Comparison method to address multi-criteria group decision-making problems. To aggregate the intuitionistic fuzzy information, we propose two aggregation operators, namely, the intuitionistic fuzzy Dombi generalised \( \lambda \)-Shapley Choquet arithmetical average operator and intuitionistic fuzzy Dombi generalised \( \lambda \)-Shapley Choquet geometric average operator. These aggregation operators consider the importance of combinations and correlations among combinations of input arguments. Furthermore, an illustrative example of a human resource management problem is presented to verify the effectiveness of the proposed method, and sensitivity and comparison analyses are conducted to demonstrate the technique’s stability and advancements. Finally, conclusions are drawn.

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Acknowledgements

The authors would like to thank the editors and anonymous reviewers for their immense help in this study. This work was supported by a Key Project of Hunan Social Science Achievement Evaluation Committee (XSP18ZDI021).

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Authors and Affiliations

  1. School of Business, Central South University, Changsha, 410083, People’s Republic of China

    Ru-xia Liang, Sang-sang He, Jian-qiang Wang & Ke Chen

  2. School of Business, Hunan University, Changsha, 410082, People’s Republic of China

    Lin Li

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  1. Ru-xia Liang
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  2. Sang-sang He
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  3. Jian-qiang Wang
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  4. Ke Chen
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Correspondence to Ke Chen.

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Liang, Rx., He, Ss., Wang, Jq. et al. An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information. Comp. Appl. Math. 38, 112 (2019). https://doi.org/10.1007/s40314-019-0886-5

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