Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China
In recent decades, rapid urbanization has introduced significant challenges to urban planning, exacerbated by ongoing urban expansion and population growth. Among these challenges is the critical need to enhance public safety and the living environment, driven by principles of human-centered design...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-08-01
|
| Series: | Frontiers of Architectural Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095263524001687 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849313544874491904 |
|---|---|
| author | Jinze Li Xiao Wang Qiyan Zhang Peng Tang |
| author_facet | Jinze Li Xiao Wang Qiyan Zhang Peng Tang |
| author_sort | Jinze Li |
| collection | DOAJ |
| description | In recent decades, rapid urbanization has introduced significant challenges to urban planning, exacerbated by ongoing urban expansion and population growth. Among these challenges is the critical need to enhance public safety and the living environment, driven by principles of human-centered design and sustainable urban development. To address this, this paper introduces a novel multi-objective optimization framework for Emergency Medical Services (EMS) facility layout, integrating multi-source data to support urban planning and manage public safety risks effectively. This framework uses corroborative multi-source data to analyze current EMS facilities and suggests improvements through preservation, expansion, and new facility introduction, carefully considering construction costs, resident usage efficiency, and access equity. A multi-objective evolutionary algorithm calculates Pareto optimal solutions for site selection, allowing for a balanced consideration of conflicting EMS siting objectives. Further solution set clustering enables decision-makers to quickly identify and refine strategies aligned with their preferences. We demonstrate the applicability of our framework through a quantitative and qualitative case study in Dangtu, China. The results reveal that our approach not only aids urban planners in making informed decisions that improve EMS facility accessibility but also ensures equitable use and enhances public safety in alignment with sustainable urban development goals. |
| format | Article |
| id | doaj-art-120fdabb3fc1453f9ce590b6c91b7bb4 |
| institution | Kabale University |
| issn | 2095-2635 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Frontiers of Architectural Research |
| spelling | doaj-art-120fdabb3fc1453f9ce590b6c91b7bb42025-08-20T03:52:43ZengKeAi Communications Co., Ltd.Frontiers of Architectural Research2095-26352025-08-011441090110710.1016/j.foar.2024.10.011Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, ChinaJinze Li0Xiao Wang1Qiyan Zhang2Peng Tang3School of Architecture, Southeast University, Nanjing 210096, China; Department of Architecture, Swiss Federal Institute of Technology Zurich (ETHZ), 8093 Zürich, SwitzerlandSchool of Architecture, Southeast University, Nanjing 210096, ChinaSchool of Architecture, Southeast University, Nanjing 210096, China; Department of Architecture, Swiss Federal Institute of Technology Zurich (ETHZ), 8093 Zürich, SwitzerlandSchool of Architecture, Southeast University, Nanjing 210096, China; Key Laboratory of Urban and Architectural Heritage Conservation (Southeast University), Ministry of Education, Nanjing 210096, China; Corresponding author. School of Architecture, Southeast University, Nanjing 210096, China.In recent decades, rapid urbanization has introduced significant challenges to urban planning, exacerbated by ongoing urban expansion and population growth. Among these challenges is the critical need to enhance public safety and the living environment, driven by principles of human-centered design and sustainable urban development. To address this, this paper introduces a novel multi-objective optimization framework for Emergency Medical Services (EMS) facility layout, integrating multi-source data to support urban planning and manage public safety risks effectively. This framework uses corroborative multi-source data to analyze current EMS facilities and suggests improvements through preservation, expansion, and new facility introduction, carefully considering construction costs, resident usage efficiency, and access equity. A multi-objective evolutionary algorithm calculates Pareto optimal solutions for site selection, allowing for a balanced consideration of conflicting EMS siting objectives. Further solution set clustering enables decision-makers to quickly identify and refine strategies aligned with their preferences. We demonstrate the applicability of our framework through a quantitative and qualitative case study in Dangtu, China. The results reveal that our approach not only aids urban planners in making informed decisions that improve EMS facility accessibility but also ensures equitable use and enhances public safety in alignment with sustainable urban development goals.http://www.sciencedirect.com/science/article/pii/S2095263524001687Location selectionEmergency Medical Services (EMS) facilityMulti-objective optimizationMulti-source data |
| spellingShingle | Jinze Li Xiao Wang Qiyan Zhang Peng Tang Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China Frontiers of Architectural Research Location selection Emergency Medical Services (EMS) facility Multi-objective optimization Multi-source data |
| title | Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China |
| title_full | Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China |
| title_fullStr | Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China |
| title_full_unstemmed | Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China |
| title_short | Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China |
| title_sort | multi objective optimization of ems facilities using multi source data a case study in dangtu china |
| topic | Location selection Emergency Medical Services (EMS) facility Multi-objective optimization Multi-source data |
| url | http://www.sciencedirect.com/science/article/pii/S2095263524001687 |
| work_keys_str_mv | AT jinzeli multiobjectiveoptimizationofemsfacilitiesusingmultisourcedataacasestudyindangtuchina AT xiaowang multiobjectiveoptimizationofemsfacilitiesusingmultisourcedataacasestudyindangtuchina AT qiyanzhang multiobjectiveoptimizationofemsfacilitiesusingmultisourcedataacasestudyindangtuchina AT pengtang multiobjectiveoptimizationofemsfacilitiesusingmultisourcedataacasestudyindangtuchina |