Title | A Hierarchical Multi-objective Programming Approach to Planning Locations for Macro and Micro Fire Stations |
Author | |
Corresponding Author | Yang,Lili |
DOI | |
Publication Years | 2022
|
ISSN | 1865-0929
|
EISSN | 1865-0937
|
Source Title | |
Volume | 1630 CCIS
|
Pages | 163-180
|
Abstract | Fire stations are among the most crucial emergency facilities in urban emergency control system in terms of their quick response to fires and other emergencies. Location planning for fire stations has a significant influence on their effectiveness and capability of emergency responses trading off with the cost of constructions. To obtain efficient and practical siting plans for fire stations, various major requirements including effectiveness maximization, distance constraint and workload limitation are required to be considered in location models. This paper proposes a novel hierarchical optimization approach taking all the major requirements for location planning into consideration and bonds functional connections between different levels of fire stations at the same time. A single-objective and a multi-objective optimization model are established coupled with genetic algorithm (GA) with elitist reservation and Pareto-based multi-objective evolutionary algorithm for model solving. The proposed hierarchical location model is further performed in a case study of Futian District in Shenzhen, and the siting results justify the effectiveness and practicality of our novel approach. |
Keywords | |
SUSTech Authorship | First
; Corresponding
|
Language | English
|
URL | [Source Record] |
Scopus EID | 2-s2.0-85140449510
|
Data Source | Scopus
|
Citation statistics |
Cited Times [WOS]:0
|
Document Type | Conference paper |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/407156 |
Department | Department of Statistics and Data Science 前沿与交叉科学研究院 |
Affiliation | 1.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,China 2.Academy for Advanced Interdisciplinary Studies,Southern University of Science and Technology,Shenzhen,China 3.Department of Computer and Information Science,University of Macau,Macao |
First Author Affilication | Department of Statistics and Data Science |
Corresponding Author Affilication | Department of Statistics and Data Science |
First Author's First Affilication | Department of Statistics and Data Science |
Recommended Citation GB/T 7714 |
Gong,Xinghan,Liang,Jun,Zeng,Yiping,et al. A Hierarchical Multi-objective Programming Approach to Planning Locations for Macro and Micro Fire Stations[C],2022:163-180.
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