TY - GEN
T1 - Location Optimization of Urban Emergency Medical Service Stations
T2 - 18th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019
AU - Song, Jiajia
AU - Li, Xiang
AU - Mango, Joseph
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Since patients’ lives are closely bound up with emergency medical services, extensive studies to improve the quality of emergency services haves been receiving special attention. This paper presents a novel hierarchical multi-objective optimization model that considers the goal of providing effectiveness equal service for all citizens firstly, reducing the total travel cost of emergency medical service missions and the number of overall stations secondly, retaining as many existing stations as possible lastly to improve both the effectiveness equity and the efficiency of emergency medical service and reduce the financial cost. New methods of chromosome coding, crossover operation and mutation operation for preserving spatial configuration of regional variables in the process of genetic algorithm are developed and used to optimize locations of EMS stations in Shanghai, China. The results demonstrate that better planning of emergency medical service stations whose service area cover all area within 4 km can reduce travel costs by 70% with 13 new built up and 8 existing stations. Due to these promising results, the new encoded methods applied in this study are not only viable but also can be used in other urban areas to improve effectiveness equity of the emergency medical service.
AB - Since patients’ lives are closely bound up with emergency medical services, extensive studies to improve the quality of emergency services haves been receiving special attention. This paper presents a novel hierarchical multi-objective optimization model that considers the goal of providing effectiveness equal service for all citizens firstly, reducing the total travel cost of emergency medical service missions and the number of overall stations secondly, retaining as many existing stations as possible lastly to improve both the effectiveness equity and the efficiency of emergency medical service and reduce the financial cost. New methods of chromosome coding, crossover operation and mutation operation for preserving spatial configuration of regional variables in the process of genetic algorithm are developed and used to optimize locations of EMS stations in Shanghai, China. The results demonstrate that better planning of emergency medical service stations whose service area cover all area within 4 km can reduce travel costs by 70% with 13 new built up and 8 existing stations. Due to these promising results, the new encoded methods applied in this study are not only viable but also can be used in other urban areas to improve effectiveness equity of the emergency medical service.
KW - Binary space mapping chromosome encoding
KW - Effectiveness equity
KW - Emergency medical service stations
KW - Hierarchical multi-objective model
KW - Location optimization
UR - https://www.scopus.com/pages/publications/85096423647
U2 - 10.1007/978-3-030-60952-8_7
DO - 10.1007/978-3-030-60952-8_7
M3 - 会议稿件
AN - SCOPUS:85096423647
SN - 9783030609511
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 68
EP - 82
BT - Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings
A2 - Di Martino, Sergio
A2 - Fang, Zhixiang
A2 - Li, Ki-Joune
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 13 November 2020 through 14 November 2020
ER -