Interruption Risk Assessment and Transmission of Fresh Cold Chain Network Based on a Fuzzy Bayesian Network-Reference-Cited by-同舟云学术

Interruption Risk Assessment and Transmission of Fresh Cold Chain Network Based on a Fuzzy Bayesian Network

Published:2021-07-01 Issue: Volume:2021 Page:1-11
ISSN:1607-887X
Container-title:Discrete Dynamics in Nature and Society
language:en
Short-container-title:Discrete Dynamics in Nature and Society

Author:

Chen Huanwan¹^ORCID,Zhang Qingnian¹^ORCID,Luo Jing¹,Zhang Xiuxia²,Chen Guopeng³

Affiliation:

1. School of Transportation, Wuhan University of Technology, Heping Road No. 1178, Wuchang District, Wuhan City WH 430063, Hubei Province, China

2. School of Modern Posts, Nanjing University of Posts and Telecommunications, 66 Xinmofan Road, Nanjing City, Jiangsu Province 210003, China

3. Planning and Operation Department, Hanjiang Water Conservancy & Hydropower Group Co., Ltd. Hanjiang Building, No. 7 Hangtian Road, Dongxihu District, Wuhan City WH 430048, Hubei Province, China

Abstract

The fresh cold chain network is complex, and the interruption risk can significantly impact it. Based on the Bayesian theory, we constructed a fresh cold chain network interruption risk topology structure. The probability of each root node was predicted and calculated based on the fuzzy set theory. The evaluation model was then validated and improved through the virus transmission model based on risk transmission. Sensitivity analysis was used to determine significant risk factors. Several strategies for minimizing interruption risks were identified.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Modelling and Simulation

Link

http://downloads.hindawi.com/journals/ddns/2021/9922569.pdf

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