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Parallel simulation and optimization framework of supplies production processes for unconventional emergencies.
Zhu, Dan; Wei, Yaoyao; Huang, Hainan; Xie, Tian.
  • Zhu D; School of Economics, Management and Law, University of South China, Hengyang, Hunan Province, China.
  • Wei Y; School of Public Administration at Nanjing Normal University, Nanjing, Jiangsu Province, China.
  • Huang H; School of Economics, Management and Law, University of South China, Hengyang, Hunan Province, China.
  • Xie T; School of Education at Central China Normal University, Wuhan, Hubei Province, China.
PLoS One ; 17(1): e0261771, 2022.
Article in English | MEDLINE | ID: covidwho-1622341
ABSTRACT
The outbreak of unconventional emergencies leads to a surge in demand for emergency supplies. How to effectively arrange emergency production processes and improve production efficiency is significant. The emergency manufacturing systems are typically complex systems, which are difficult to be analyzed by using physical experiments. Based on the theory of Random Service System (RSS) and Parallel Emergency Management System (PeMS), a parallel simulation and optimization framework of production processes for surging demand of emergency supplies is constructed. Under this novel framework, an artificial system model paralleling with the real scenarios is established and optimized by the parallel implementation processes. Furthermore, a concrete example of mask shortage, which occurred at Huoshenshan Hospital in the COVID-19 pandemic, verifies the feasibility of this method.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / Emergency Service, Hospital Type of study: Randomized controlled trials Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: JOURNAL.PONE.0261771

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / Emergency Service, Hospital Type of study: Randomized controlled trials Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: JOURNAL.PONE.0261771