A Hybrid Algorithm for the Equal Districting Problem

Kong, Yali

doi:10.1007/978-3-030-85462-1_9

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…In the same year, Jiang et al considered how negative factors, such as current fire risk, land cover, the spatial distribution of fire stations, and traffic congestion, affect the choice of fire station location [1]. The locations of optimized facilities are mainly divided into the following types: commercial enterprise location [16,17], fire station location [18][19][20], medical facility location [21][22][23], school location, and school district division [24][25][26]. In addition, one must consider airport locations [27], the optimal layout of rural settlements [28,29], transport-hub locations [30], refuge location [31], logistics distribution centers, etc.…”

Section: Introductionmentioning

confidence: 99%

Multi-Criterion Spatial Optimization of Future Police Stations Based on Urban Expansion and Criminal Behavior Characteristics

Jiang

Guo²,

Yan³

2022

IJGI

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Lanzhou’s rapid development has raised new security challenges, and improving public safety in areas under the jurisdiction of police stations is an effective way to address the problem of public security in urban areas. Unfortunately, the existing studies do not consider how factors such as future land changes, building functions, and characteristics of criminal behavior influence the choice of areas for police stations and the optimization of police stations with respect to traffic congestion. To solve these problems, we apply multiple methods and multi-source geospatial data to optimize police station locations. The proposed method incorporates a big data perspective, which provides new ideas and technical approaches to site selection models. First, we use the central city of Lanzhou as the study area and erase the exclusion areas from the initial layer to identify the undeveloped areas. Second, historical crime data, point of interest, and other data are combined to assess the potential crime risk. We then use the analytic hierarchy process to comprehensively assess undeveloped areas based on potential crime hotspots and on socioeconomic drivers and orography. In addition, according to China’s Road Traffic Safety Law and the current traffic congestion in the city, a minimum speed is determined, so that the target area can be reached in time even in congested traffic. Finally, we draw the spatial coverage map of police stations based on the location-allocation model and network analysis and optimize the map by considering the coverage rate of high-risk areas and building construction, in addition to maintenance and other objectives. The result shows that crime concentrates mainly in densely populated areas, indicating that people and wealth are the main drivers of crime. The differences in the spatial distribution of crime hotspots and residential areas at different spatial scales mean that the ratio of public security police force to household police force allocated to different police stations is spatially nonuniform. The method proposed herein reduces the overlap of police station service areas by 22.8% and increases the area coverage (12.01%) and demand point coverage (7.25%). The area coverage means an area potentially accessible within five minutes, and point coverage implies an effective drive. Within reasonable optimization, this allows us to eventually remove 13 existing police stations and add 24 candidate police stations.

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Section: Introductionmentioning

confidence: 99%

Multi-Criterion Spatial Optimization of Future Police Stations Based on Urban Expansion and Criminal Behavior Characteristics

Jiang

Guo²,

Yan³

2022

IJGI

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“…It can allow the relevant resources to be fully utilized [1]. Important criteria for districting are design balance, compactness and continuity of the areas [2][3][4]. The districting problem is applied to all aspects of politics, economics, the environment and public services [5,6].…”

Section: Introductionmentioning

confidence: 99%

A hybrid spectral clustering simulated annealing algorithm for the street patrol districting problem

Jiang

Zhao

et al. 2022

Complex Intell. Syst.

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Reasonable districting plays an important role in the patrolling process. In this paper, workload attributes are considered, and a mixed integer programming model is developed to solve the street patrol districting problem (SPDP). The improved spectral clustering algorithm named spectral clustering algorithm based on the road network (SCRn) and simulated annealing algorithm (SA) are combined. This results in a hybrid algorithm called SCRn-SA. The SCRn-SA algorithm is tested on small examples and real instances in Zhengzhou, China. The experimental results show that the proposed algorithm is effective for solving SPDP. It has better performance when compared to other advanced algorithms.

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Variants of Location-Allocation Problems for Public Service Planning

Kong

2022

New Thinking in GIScience

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A Hybrid Algorithm for the Equal Districting Problem

Cited by 4 publications

References 23 publications

Multi-Criterion Spatial Optimization of Future Police Stations Based on Urban Expansion and Criminal Behavior Characteristics

Multi-Criterion Spatial Optimization of Future Police Stations Based on Urban Expansion and Criminal Behavior Characteristics

A hybrid spectral clustering simulated annealing algorithm for the street patrol districting problem

Variants of Location-Allocation Problems for Public Service Planning

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