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Parallel simulation and optimization framework of supplies production processes for unconventional emergencies
Dan Zhu1,2, Yaoyao Wei1,3, Hainan Huang1
1School of Economics, Management and Law, University of South China, Hengyang, Hunan Province, China.
Plos One
|January 13, 2022
Summary
This study introduces a novel framework for optimizing emergency supply production during crises. The method uses parallel simulation to improve efficiency when demand surges, as demonstrated with a mask shortage example.
Area of Science:
- Operations Research
- Supply Chain Management
- Emergency Management
Background:
- Unconventional emergencies cause rapid increases in demand for critical supplies.
- Analyzing complex emergency manufacturing systems through physical experiments is often infeasible.
- Effective arrangement of production processes and efficiency improvement are crucial.
Purpose of the Study:
- To construct a parallel simulation and optimization framework for emergency supply production processes.
- To address the challenges of complex emergency manufacturing systems.
- To improve production efficiency during surging demand.
Main Methods:
- Utilized the theory of Random Service System (RSS).
- Employed the Parallel Emergency Management System (PeMS) framework.
- Developed an artificial system model paralleling real-world scenarios for optimization via parallel implementation.
Main Results:
- A novel parallel simulation and optimization framework was successfully constructed.
- The artificial system model effectively paralleled real scenarios.
- The framework demonstrated feasibility in optimizing production processes for surging demand.
Conclusions:
- The proposed framework offers an effective approach for analyzing and optimizing emergency manufacturing systems.
- The method is particularly useful for complex systems where physical experimentation is not viable.
- The framework's feasibility was validated through a real-world case study of mask shortages during the COVID-19 pandemic.
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