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Investigation of multiple heterogeneous relationships using a q-rung orthopair fuzzy multi-criteria decision algorithm

  • S. I : Hybridization of Neural Computing with Nature Inspired Algorithms
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Abstract

Q-rung orthopair fuzzy (q-ROF) set is one of the powerful tools for handling the uncertain multi-criteria decision-making (MCDM) problems, various MCDM methods under q-ROF environment have been developed in recent years. However, most existing studies merely concerned about the relationship between the criteria but they have not investigated the interactions between membership function and non-membership function. To explore the multiple heterogeneous relationships among membership functions and criteria, we propose a novel decision algorithm based on q-ROF set to deal with these using interactive operators and Maclaurin symmetric mean (MSM) operators. Specifically, the new interaction laws in the membership pairs of q-ROF sets are explained, and their properties are analyzed as the initial stage. Then, taking into account the influence of two or more factors on decision analysis, a q-ROF interaction Maclaurin symmetry mean (q-ROFIMSM) operator is formed based on the proposed interaction law to identify these factors’ interrelationship. Thirdly, based on the proposed operator with q-ROF information, a MCDM algorithm is developed and illustrated by numerical examples. An analysis of the feasibility, sensitivity, and superiority of the proposed framework is provided to validate our proposed method.

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Acknowledgements

This work was supported in part by the Natural Science Foundation of China (No. 71704007), the Beijing Social Science Foundation of China (No. 18GLC082), and University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province (No. 2017103).

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Authors and Affiliations

  1. College of Economics and Management, Beijing University of Technology, Beijing, China

    Zaoli Yang

  2. School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala, India

    Harish Garg

  3. College of Economics and Management, Harbin Engineering University, Harbin, China

    Jinqiu Li

  4. Department of Mathematics and Computer Science, Brandon University, Brandon, Canada

    Gautam Srivastava

  5. Research Centre of Interneural Computing, China Medical University, Taichung City, Taiwan

    Gautam Srivastava

  6. Discipline of ICT, College of Sciences and Engineering, University of Tasmania, Hobart, Australia

    Zehong Cao

  7. School of Computer Science, University of Technology Sydney, Sydney, Australia

    Zehong Cao

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  1. Zaoli Yang
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  2. Harish Garg
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  3. Jinqiu Li
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  4. Gautam Srivastava
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  5. Zehong Cao
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Correspondence to Harish Garg or Zehong Cao.

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Yang, Z., Garg, H., Li, J. et al. Investigation of multiple heterogeneous relationships using a q-rung orthopair fuzzy multi-criteria decision algorithm. Neural Comput & Applic 33, 10771–10786 (2021). https://doi.org/10.1007/s00521-020-05003-5

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  • DOI: https://doi.org/10.1007/s00521-020-05003-5

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