Abstract

The healthcare resources supply network design for resilience is an effective way to deal with uncertainty disruption. In this article we propose a model of supply network self-organization evolution, and establish self-organized criticality as a cause of cascade failure. Our main purpose is to keep the system in a resilient range, i.e., critical state. A network structural design with smaller degree distribution exponent can achieve better absorptive capacity at macro level. An interactive rule design with extremal optimization has better adaptive capacity at micro level. Using macro statistic and indicator micro performance indicator, we demonstrate that our design can slow the development to a supercritical state and can improve the resilience of the supply network.

Highlights

  • A novel coronavirus (2019-nCoV)-infected pneumonia has been detected in over 10 million patients and has claimed more than half a million lives as of 30 June 2020

  • The method slows down the development of supercritical system

  • This way can eliminate the the resilience of supply network (SN) increased by 16.09%

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Summary

Introduction

A novel coronavirus (2019-nCoV)-infected pneumonia has been detected in over 10 million patients and has claimed more than half a million lives as of 30 June 2020. Due to the lack of healthcare resources, the reliable design of healthcare resources supply network (HRSN) has attracted significant attention [2]. It is of greatly difficult to improve the design and the management of healthcare resources supply networks. Designing a resilient supply network is an effective way to cope with disruptions [5]. Supply network design includes the numbers, locations, and capacities of enterprises and the quantity of flow between them. These designs mainly pay attention to improve the network performance, rather than to improve the SN resilience. SOC has become a theory to explain the cascading failure, and can effectively influence the design of supply network to maximize its resilience.

Supply Network Resilience
SN Resilience Design
The Relationship between Self-Organized Criticality and Resilience
Self-Organized
The Parameters of the Model
Initial
Cascade Failure
Design for SN Resilience
Network Structure Design
Design for Interaction Rules
Case Background
SOC in the HRSN
Conclusion
The Influence of Network Structure Design for Resilience
15. Although
As in the Figure sizes obeylaw theindex power
16. Avalanche
The Influence of Interactive Rule Design for Resilience
Findings
Conclusions
Full Text
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