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Algorithms 2018, 11(3), 29; https://doi.org/10.3390/a11030029

Dombi Aggregation Operators of Neutrosophic Cubic Sets for Multiple Attribute Decision-Making

Department of Electrical and Information Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing 312000, China
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Received: 7 February 2018 / Revised: 2 March 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
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Abstract

The neutrosophic cubic set can describe complex decision-making problems with its single-valued neutrosophic numbers and interval neutrosophic numbers simultaneously. The Dombi operations have the advantage of good flexibility with the operational parameter. In order to solve decision-making problems with flexible operational parameter under neutrosophic cubic environments, the paper extends the Dombi operations to neutrosophic cubic sets and proposes a neutrosophic cubic Dombi weighted arithmetic average (NCDWAA) operator and a neutrosophic cubic Dombi weighted geometric average (NCDWGA) operator. Then, we propose a multiple attribute decision-making (MADM) method based on the NCDWAA and NCDWGA operators. Finally, we provide two illustrative examples of MADM to demonstrate the application and effectiveness of the established method. View Full-Text
Keywords: neutrosophic cubic sets; neutrosophic cubic Dombi weighted arithmetic average (NCDWAA) operator; Dombi operations; multiple attribute decision-making; neutrosophic cubic Dombi weighted geometric average (NCDWGA) operator neutrosophic cubic sets; neutrosophic cubic Dombi weighted arithmetic average (NCDWAA) operator; Dombi operations; multiple attribute decision-making; neutrosophic cubic Dombi weighted geometric average (NCDWGA) operator
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Shi, L.; Ye, J. Dombi Aggregation Operators of Neutrosophic Cubic Sets for Multiple Attribute Decision-Making. Algorithms 2018, 11, 29.

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