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Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm

INTRODUCTION: Shelter allocation is one of the most important measures in urban disaster prevention and mitigation planning. Meanwhile, it is essentially a comprehensive planning problem combining resource allocation and traffic routing. A reasonable allocation scheme can avoid congestion, improve e...

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Detalles Bibliográficos
Autores principales: Yin, Yang, Zhao, Xiangcheng, Lv, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859660/
https://www.ncbi.nlm.nih.gov/pubmed/36684895
http://dx.doi.org/10.3389/fpubh.2022.1098675
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author Yin, Yang
Zhao, Xiangcheng
Lv, Wei
author_facet Yin, Yang
Zhao, Xiangcheng
Lv, Wei
author_sort Yin, Yang
collection PubMed
description INTRODUCTION: Shelter allocation is one of the most important measures in urban disaster prevention and mitigation planning. Meanwhile, it is essentially a comprehensive planning problem combining resource allocation and traffic routing. A reasonable allocation scheme can avoid congestion, improve evacuation efficiency, and reduce the casualty rate. Owing to the large region and large evacuation population demand, quickly solving the complex allocation problem is somewhat challenging, and thus, the optimal results are difficult to obtain with the increase of evacuation scale by traditional allocation methods. METHODS: This article aims to establish a shelter allocation model for large-scale evacuation, which employs an improved quantum genetic algorithm (IQGA) based on spreading operation and considering the total evacuation distance, the capacity constraint of evacuation sites, and the dispersion of allocation results, and compare allocation schemes of the spreading model with those of models that consider different constraints. RESULTS AND DISCUSSION: Results show that the allocation model with the spreading operation has better allocation results than that without the spreading operation. For the allocation model with spreading operation, the spreading model with different spreading speeds is more reasonable than that with the same spreading speed, and the allocation results are closer to the ideal results with the increase of constraints. In addition, according to the allocation results, the evacuation route map and the evacuation heat map are drawn to intuitively understand the distribution scheme of each shelter.
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spelling pubmed-98596602023-01-21 Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm Yin, Yang Zhao, Xiangcheng Lv, Wei Front Public Health Public Health INTRODUCTION: Shelter allocation is one of the most important measures in urban disaster prevention and mitigation planning. Meanwhile, it is essentially a comprehensive planning problem combining resource allocation and traffic routing. A reasonable allocation scheme can avoid congestion, improve evacuation efficiency, and reduce the casualty rate. Owing to the large region and large evacuation population demand, quickly solving the complex allocation problem is somewhat challenging, and thus, the optimal results are difficult to obtain with the increase of evacuation scale by traditional allocation methods. METHODS: This article aims to establish a shelter allocation model for large-scale evacuation, which employs an improved quantum genetic algorithm (IQGA) based on spreading operation and considering the total evacuation distance, the capacity constraint of evacuation sites, and the dispersion of allocation results, and compare allocation schemes of the spreading model with those of models that consider different constraints. RESULTS AND DISCUSSION: Results show that the allocation model with the spreading operation has better allocation results than that without the spreading operation. For the allocation model with spreading operation, the spreading model with different spreading speeds is more reasonable than that with the same spreading speed, and the allocation results are closer to the ideal results with the increase of constraints. In addition, according to the allocation results, the evacuation route map and the evacuation heat map are drawn to intuitively understand the distribution scheme of each shelter. Frontiers Media S.A. 2023-01-06 /pmc/articles/PMC9859660/ /pubmed/36684895 http://dx.doi.org/10.3389/fpubh.2022.1098675 Text en Copyright © 2023 Yin, Zhao and Lv. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Yin, Yang
Zhao, Xiangcheng
Lv, Wei
Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
title Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
title_full Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
title_fullStr Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
title_full_unstemmed Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
title_short Emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
title_sort emergency shelter allocation planning technology for large-scale evacuation based on quantum genetic algorithm
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859660/
https://www.ncbi.nlm.nih.gov/pubmed/36684895
http://dx.doi.org/10.3389/fpubh.2022.1098675
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