Inicio  /  Applied Sciences  /  Vol: 13 Par: 13 (2023)  /  Artículo
ARTÍCULO
TITULO

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

Thi-Phuong Nguyen    
Chin-Lung Huang and Yi-Kuei Lin    

Resumen

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.

 Artículos similares

       
 
Shaoyan Zuo, Dazhi Wang, Xiao Wang, Liujia Suo, Shuaiwu Liu, Yongqing Zhao and Dewang Liu    
In this study, a deep learning network for extracting spatial-temporal features is proposed to estimate significant wave height (???? H s ) and wave period (???? T s ) from X-band marine radar images. Since the shore-based radar image in this study is in... ver más

 
Xie Lian, Xiaolong Hu, Liangsheng Shi, Jinhua Shao, Jiang Bian and Yuanlai Cui    
The parameters of the GR4J-CemaNeige coupling model (GR4neige) are typically treated as constants. However, the maximum capacity of the production store (parX1) exhibits time-varying characteristics due to climate variability and vegetation coverage chan... ver más
Revista: Water

 
Han Zhang, Yadong Wu, Weihan Zhang and Yuling Zhang    
The precise ascertainment of stellar ages is pivotal for astrophysical research into stellar characteristics and galactic dynamics. To address the prevalent challenges of suboptimal accuracy in stellar age determination and limited proficiency in apprehe... ver más
Revista: Applied Sciences

 
Tomasz Gajewski and Pawel Skiba    
The main goal of this work is to combine the usage of the numerical homogenization technique for determining the effective properties of representative volume elements with artificial neural networks. The effective properties are defined according to the... ver más
Revista: Applied Sciences

 
Rohan S. Sharma and Serhat Hosder    
The intent of this work was to investigate the feasibility of developing machine learning models for calculating values of airplane configuration design variables when provided time-series, mission-informed performance data. Shallow artificial neural net... ver más
Revista: Aerospace