ArticleInternational journal of environmental research and public health2018
Decision Analysis of Disturbance Management in the Process of Medical Supplies Transportation after Natural Disasters.
Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 14 citations in OpenAlex.
- Enhancing disaster response through comprehensive transportation models: insights from the Kahramanmaraş earthquakes.Scandinavian journal of trauma, resuscitation and emergency medicine · 2023Article
- Identifying resilience strategies for disruption management in the healthcare supply chain during COVID-19 by digital innovations: A systematic literature review.Informatics in medicine unlocked · 2023Review
- Research Frontiers of Health Emergency and Disaster Risk Management: What Do We Know So Far?International journal of environmental research and public health · 2020Article
- Multi-Depot Open Vehicle Routing Problem with Time Windows Based on Carbon Trading.International journal of environmental research and public health · 2018Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Public health emergencies, such as casualties and epidemic spread caused by natural disasters, have become important factors that seriously affect social development. Special medical supplies, such as blood and vaccines, are important public health medical resources, and the cold-chain distribution of medical supplies is in a highly unstable environment after a natural disaster that is easily affected by disturbance events. This paper innovatively studies the distribution optimization of medical supplies after natural disasters from the perspective of disturbance management. A disturbance management model for medical supplies distribution is established from two dimensions: time and cost. In addition, a hybrid genetic algorithm is introduced to solve the model. Disturbance recovery schemes with different weight coefficients are obtained through the actual numerical experiments, and experimental results show the effectiveness of the proposed model and algorithm. Finally, we discuss the formulation of weight coefficients in the case of emergency distribution and general distribution, which provide a reference for emergency decisions in disturbance events.
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Registered trials
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