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Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean

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Abstract

In this paper, we proposed a single-valued neutrosophic normalized weighted Bonferroni mean (SVNNWBM) operator on the basis of Bonferroni mean, the weighted Bonferroni mean (WBM), and the normalized WBM. Firstly, the definition, operational laws, characteristics, and comparing method of single-valued neutrosophic numbers (SVNNs) are introduced. Then, the SVNNWBM operator is developed, and some properties and special cases of this operator are analyzed. Furthermore, an approach is developed to solve the multiple attribute decision-making problems with SVNNs based on the SVNNWBM operator. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (No. 71271124), the Humanities and Social Sciences Research Project of Ministry of Education of China (No. 13YJC630104), Shandong Provincial Social Science Planning Project (No. 13BGLJ10), the Natural Science Foundation of Shandong Province (No. ZR2011FM036), and Graduate education innovation projects in Shandong Province (SDYY12065). The authors also would like to express appreciation to the anonymous reviewers and Editor in Editor for their very helpful comments that improved the paper.

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Authors and Affiliations

  1. School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, 250014, Shandong, China

    Peide Liu & Yumei Wang

  2. School of Economics and Management, Civil Aviation University of China, Tianjin, 300300, China

    Peide Liu

Authors
  1. Peide Liu
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  2. Yumei Wang
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Correspondence to Peide Liu.

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Liu, P., Wang, Y. Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean. Neural Comput & Applic 25, 2001–2010 (2014). https://doi.org/10.1007/s00521-014-1688-8

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  • DOI: https://doi.org/10.1007/s00521-014-1688-8

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