A Framework for Triangular Fuzzy Random Multiple-Criteria Decision Making

Chen, Zhen‐Song; Chin, Kwai‐Sang; Li, Yanlai

doi:10.1007/s40815-015-0109-1

Cited by 6 publications

(2 citation statements)

References 61 publications

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“…In the process of investment decision making, randomness and fuzziness are important uncertainties affecting the final decision making. Given the inaccuracy of certain precision formulas proposed in previous studies for the variance of a triangular fuzzy random variable (FRV), Chen et al ( 2016 ) presented the detailed process of calculating precision variance formulas and discussed several properties of the expectation and variance of triangular FRVs. Hao et al ( 2008 ) presented a method to calculate precision formulas of an FRV that can design algorithms that solved fuzzy random programming and handled fuzzy random optimization problems.…”

Section: Introductionmentioning

confidence: 99%

A novel fuzzy dominant goal programming for portfolio selection with systematic risk and non-systematic risk

Deng

Yuan

2021

Soft Comput

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In this paper, we consider a fuzzy portfolio selection problem with systematic risk and non-systematic risk simultaneously. These two kinds of risks are measured by beta coefficient and random error variance obtained by Sharp Single Index Model. The total risk as the objective of portfolio decision is obtained by weighting the two kinds of risk. Among them, the weight of systematic risk is regarded as the degree of investors' attention to system risk in economic sense. In addition, the fuzzy return and the degree of diversification are measured by triangular fuzzy number and entropy, respectively. And they are also considered the goal of investment decisions. Hence, a tri-objective portfolio is proposed in this paper. For the fuzzy objectives in the model, a goal programming method based on fuzzy dominance is proposed, which can help investors better capture the ideal point of fuzzy returns according to their risk preference. Finally, combined with the systematic impact of COVID-19 on the financial market, we make an empirical analysis based on our proposed model. The results show that the total risk will be on the high side when value is too large or too small. That means paying too much or little attention to the systematic risk will lead investors to bear more risk. In addition, when investors ignore the systematic risk; that is, the value is low, and investors will concentrate their funds in the same industry.

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Section: Introductionmentioning

confidence: 99%

A novel fuzzy dominant goal programming for portfolio selection with systematic risk and non-systematic risk

Deng

Yuan

2021

Soft Comput

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“…Using this concept of fuzzy graph, Koczy 10 used fuzzy graphs in the optimization of networks. For further details of fuzzy graphs, readers may look in 7,9,11,12,15,16,17,18,19,20,21,22,23,27 .…”

Section: Introductionmentioning

confidence: 99%

Generalized fuzzy trees

Sarkar¹,

Samanta²

2017

IJCIS

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Graphs are the backbone of many real systems like social networks, image segmentation, scheduling, etc. To input uncertainty to such systems, generalized fuzzy graphs are used. Generalized fuzzy tree is one generalized fuzzy subgraph of a generalized fuzzy graph which characterizes the whole graph. In this study, generalized fuzzy trees are introduced. The concepts of strongly connectedness, nearly disconnect, distance between two nodes, bridges are exemplified.

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