1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China 2. The Architectural Design and Research Institute of Zhejiang University Co. Ltd, Hangzhou 310028, China 3. School of Public Affairs, Zhejiang University, Hangzhou 310058, China 4. The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China 5. School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China 6. Center for Balance Architecture, Zhejiang University, Hangzhou 310027, China
Based on the recorded data of nucleic acid testing points in the Shangcheng district of Hangzhou in 2022, and dividing Shangcheng district into 10 786 population points (50 m×50 m), an optimized non-dominated sorting genetic algorithm III (NSGA3) was used to simulate the collective emergency behavior of each population point moving towards nearby nucleic acid testing points. This simulation was carried out with 50 000 iterations, and the kernel density analysis was performed on the iteration results. The optimization results of the 15-minute living circle based on a single facility point, the optimization results of the 15-minute living circle based on dual facility points, the optimization results of the facility points based on the needs of the elderly, and the optimization results of the 5-minute living circle based on a single facility point were obtained. Results showed that, taking the optimization results of the 15-minute living circle based on a single facility point as an example, without changing the service capacity, the average accessibility time of the facilities was optimized from 292.44 s to 264.62 s by the iterated nucleic acid testing points network through the optimized NSGA3 algorithm. A fuzzy site selection range for urban emergency facilities based on the results was formed. The spatial pattern of "agglomeration at the micro level and dispersion at the macro level" was identified. These results of fuzzy site selection range could be subsequently transformed into a "community-level multifunctional emergency space", which can provide theoretical advice for site selection decisions for temporary emergency facilities in the event of future emergencies.
Fig.1Overall technical roadmap for research on range of fuzzy site selection based on NSGA3
Fig.2Optimized NSGA3 algorithm framework based on objective function
Fig.3Analysis chart of point kernel density of 50000 iterations under NSGA3 algorithm
Fig.4Analysis of point kernel density of 50000 iterations under NSGA3 algorithm after facility point doubling
Fig.5Analysis chart of point kernel density of 50000 iterations under NSGA3 algorithm modified based on adaptive aging requirements
Fig.6Analysis chart of point kernel density of 50000 iterations based on 5-minute perspective
Fig.7Distribution of 32 point aggregation areas generated based on kernel density analysis
分区
$\bar t $/s
σ($\bar t $)/s
J
1
248.0774
2.7433
10
2
270.3496
0.3513
15
3
248.7042
1.2124
12
4
276.4531
2.1290
5
5
297.8310
0.1557
7
6
288.0829
0.1442
10
7
217.0312
0.3313
7
8
274.8616
0.1913
11
9
287.9544
0.4319
5
10
288.8078
0.1338
3
11
287.0793
0.0579
5
12
295.4084
0.3039
3
13
215.6401
0.0530
8
14
271.3761
0.3804
9
15
291.9606
0.3333
6
16
293.0717
0.0000
1
17
277.6505
0.2215
6
18
264.0542
0.6073
10
19
259.5588
0.5181
3
20
245.3588
0.1252
5
21
290.0910
0.3998
6
22
319.1667
0.0000
1
23
253.9780
0.4798
6
24
285.1999
0.3913
3
25
233.4427
0.3667
2
26
264.7986
0.6493
12
27
265.2594
0.5204
4
28
281.2926
0.0436
3
29
230.2947
2.4052
10
30
251.5801
1.5459
7
31
255.2819
3.0509
6
32
255.0366
0.0000
1
Tab.1Statistical table of point aggregation areas’ reachable time based on optimization results of 15-minute living circle based on single facility point
Fig.8Fuzzy site selection range of facility points based on kernel density analysis
Fig.9Demonstration of Xiaoying Street planning case: 15-minute living circle facilities planning map
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