Algorithm Research & Explore
|
2996-3000

Scheme optimum model in investment decision-making based on single-valued neutrosophic set

Liu Qing1
Hua Xiaohui2
1. School of Mathematics & Statistics, Xinxiang University, Xinxiang Henan 453003, China
2. College of Mathematics & Information Science, Henan Normal University, Xinxiang Henan 453007, China

Abstract

In order to optimize the optimization model of investment decision scheme, this paper proposed a new method for multi-attribute decision making based on single-valued neutrosophic environment. Firstly, it gave a generalized distance formula based on single-valued neutrosophic set. Next it determined the weights of decision-making experts and attribute index by the language variable. Then it constructed the weighted comprehensive decision matrix. Furthermore, it calculated the distance between all alternatives and the ideal solution, and then used the relative closeness degree function to sort the alternatives and get the optimal decision scheme. Finally, to show the validity and practicability of the model, it gave an illustrative example for optimization of investment decision scheme as an application of the model.

Foundation Support

国家自然科学基金资助项目(115010176)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.05.0186
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 10
Section: Algorithm Research & Explore
Pages: 2996-3000
Serial Number: 1001-3695(2020)10-023-2996-05

Publish History

[2020-10-05] Printed Article

Cite This Article

刘庆, 化小会. 基于单值中智集的投资决策方案优选模型 [J]. 计算机应用研究, 2020, 37 (10): 2996-3000. (Liu Qing, Hua Xiaohui. Scheme optimum model in investment decision-making based on single-valued neutrosophic set [J]. Application Research of Computers, 2020, 37 (10): 2996-3000. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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