Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88685
Title: A network-based impact measure for propagated losses in a supply chain network consisting of resilient components
Authors: Valenzuela, Jesus Felix Bayta
Fu, Xiuju
Xiao, Gaoxi
Goh, Rick Siow Mong
Keywords: Supply Chain Network
Resilient Components
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Valenzuela, J. F. B., Fu, X., Xiao, G., & Goh, R. S. M. (2018). A Network-Based Impact Measure for Propagated Losses in a Supply Chain Network Consisting of Resilient Components. Complexity, 2018, 1724125-. doi:10.1155/2018/1724125
Series/Report no.: Complexity
Abstract: The topology of a supply chain network affects the impacts of disruptions in it. We formulate a network-based measure of the impact of a disruption loss in a supply chain propagating downstream from an originating node. The measure takes into account the loss profile of the originating node, the structure of the supply network, and the resilience of the network components. We obtain an analytical expression for the impact measure under a beta-distributed initial loss (generalizable to any continuous distribution supported on the interval ), under a breakthrough scenario (in which a fraction of the initial production loss reaches a focal company downstream as opposed to containment upstream or at the originating point). Furthermore, we obtain a closed-form solution for a supply chain network with a -ary tree topology; a numerical study is performed for a scale-free network and a random network. Our proposed approach enables the evaluation of potential losses for a focal company considering its supply chain network structure, which may help the company to plan or redesign a robust and resilient network in response to different types of disruptions.
URI: https://hdl.handle.net/10356/88685
http://hdl.handle.net/10220/45855
ISSN: 1076-2787
DOI: 10.1155/2018/1724125
Schools: School of Electrical and Electronic Engineering 
Rights: © 2018 Jesus Felix Bayta Valenzuela et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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