ArticleScientific reports2021
Routing algorithms as tools for integrating social distancing with emergency evacuation.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 15 citations in OpenAlex.
- Experimental study on the synchronization mechanism and trigger characteristic density of vertical evacuation in crowds.Scientific reports · 2024Article
- Research on origin-based cold storage location and routing optimization of fresh agricultural products based on hybrid whale algorithm.Scientific reports · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
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Abstract
One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe this evacuation process as a Capacitated Vehicle Routing Problem (CVRP) and solve it using a DNN (Deep Neural Network)-based solution (Deep Reinforcement Learning) and a non-DNN solution (Sweep Algorithm). A central question is whether Deep Reinforcement Learning provides sufficient extra routing efficiency to accommodate increased social distancing in a time-constrained evacuation operation. We found that, in comparison to the Sweep Algorithm, Deep Reinforcement Learning can provide decision-makers with more efficient routing. However, the evacuation time saved by Deep Reinforcement Learning does not come close to compensating for the extra time required for social distancing, and its advantage disappears as the emergency vehicle capacity approaches the number of people per household.
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Registered trials
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