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Improved q-rung orthopair fuzzy line integral aggregation operators and their applications for multiple attribute decision making

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Abstract

The q-rung orthopair fuzzy line integral (q-ROFLI) operator is a potent mathematical tool to aggregate non-standard fuzzy information in the process of Decision Making. To overcome some disadvantages of the q-rung orthopair fuzzy integral curves (q-ROFICs) which was proposed by Gao et al. (IEEE Trans Cybern, https://doi.org/10.1109/TCYB.2019.290865, 2019), in this paper, we present a novel definition of q-ROFICs. Based on this notion, we give a completed definition for q-ROFLI. Furthermore, we give a Newton–Leibniz formula through the q-rung orthopair fuzzy function with the variable upper limit (VUL-q-ROFF), and investigate the intermediate value theorem which can be utilized to solve generalized mean value theorem. Moreover, we propose the q-rung orthopair fuzzy line integral aggregation (q-ROFLIA) operator, and an improved q-ROFLIA with reliability (R-q-ROFLIA) operator. As their applications, we give several examples to show the process for aggregating q-rung orthopair fuzzy data by these operators. At last, the validity and flexibility of the above operators are verified through a practical example, especially the superiority of R-q-ROFLIA can avoid losing important extreme data, and make the results more suitable for the practical Decision Making.

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Acknowledgements

The authors would like to thank the referees for their invaluable suggestions, which put the article in its present shape. Also, the authors are thankful to the NICE: NRT for Integrated Computational Entomology, US NSF award 1631776.

Funding

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61806030, 61936001 and 61876201. The National Key Research and Development Program of China under Grant No. 2019QY(Y)0301. The Natural Science Foundation of Chongqing under Grant Nos. cstc2019jcyjmsxmX0485 and cstc2019jcyj-cxttX0002.

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Authors and Affiliations

  1. School of Science, Chongqing University of Posts and Telecommunications, Chongqing, 400065, People’s Republic of China

    Yabin Shao

  2. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, People’s Republic of China

    Junle Zhuo

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  1. Yabin Shao
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  2. Junle Zhuo
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YS contributed to the data analysis work and checked the whole manuscript. JZ performed the simulations and wrote this manuscript. All authors revised and approved the publication.

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Correspondence to Yabin Shao.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Shao, Y., Zhuo, J. Improved q-rung orthopair fuzzy line integral aggregation operators and their applications for multiple attribute decision making. Artif Intell Rev 54, 5163–5204 (2021). https://doi.org/10.1007/s10462-021-10017-z

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