AUTHOR=Yin Yang , Zhao Xiangcheng , Lv Wei 

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

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.1098675

DOI=10.3389/fpubh.2022.1098675

ISSN=2296-2565

ABSTRACT=The shelters allocation is one of the most important measures in urban disaster prevention and mitigation planning, meanwhile it is essentially a comprehensive planning problem combining the resource allocation and traffic routing. A reasonable allocation scheme can avoid congestion, improve evacuation efficiency and reduce casualty rate. Owing to the large region and large evacuation population demand, quickly solve 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. The aim of this paper is to establish a shelters allocation model in the large-scale evacuation, which employing an improved quantum genetic algorithm (IQGA) based on spreading operation as well as considering the total evacuation distance, the capacity constraint of evacuation sites, and the dispersion of allocation results. Compared allocation schemes of spreading model with those of models that considering different constraint. Results show that the allocation model with spreading operation has better allocation results than that without spreading operation. For the allocation model with spreading operation, the spreading model with different spreading speed is more reasonable than that with 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 evacuation heat-map are drawn for intuitively understanding the distribution scheme of each shelter.