Estimation of the Network Reliability for a Stochastic Cold Chain Network with Multi-State Travel Time-Reference-Cited by-同舟云学术

Estimation of the Network Reliability for a Stochastic Cold Chain Network with Multi-State Travel Time

Published:2023-07-05 Issue:13 Volume:13 Page:7897
ISSN:2076-3417
Container-title:Applied Sciences
language:en
Short-container-title:Applied Sciences

Author:

Nguyen Thi-Phuong¹,Huang Chin-Lung²,Lin Yi-Kuei²³⁴⁵

Affiliation:

1. Master Program in Smart Manufacturing and Applied Information Science, National Chin-Yi University of Technology, Taichung 411070, Taiwan

2. Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan

3. Department of Business Administration, Asia University, Taichung 413305, Taiwan

4. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 404333, Taiwan

5. Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 413310, Taiwan

Abstract

A stochastic cold chain (SCC) is a common supply chain in real life that emphasizes the need for commodities to arrive fresh within time constraints. In previous research on supply chains, the time factor was regarded as a fixed number. However, the travel time is a stochastic factor due to traffic and weather conditions during the delivery. Therefore, this paper concentrates on the two multi-state factors simultaneously. Network reliability is one of the performance indexes used to assess the cold chain efficacy, defined as the probability that the flow of SCC can satisfy the demand within the delivery time threshold. The SCC with two multi-state factors is modeled as a stochastic cold chain network with multi-state travel time (SCCNMT). To calculate the network reliability of an SCCNMT, we will calculate the demand reliability and time reliability separately, treating them as independent events, and multiply the demand and time reliability to estimate the network reliability of the two multi-state factors.

Funder

National Science and Technology Council Taiwan

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Link

https://www.mdpi.com/2076-3417/13/13/7897/pdf

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