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Use of different optimization algorithms to define service areas of police stations in Portugal
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Orientador(es)
Resumo(s)
Security is considered a fundamental right in democratic societies. Nowadays security forces reorganization depends on the population distribution and dynamics. The spatial disposition of security forces and the corresponding adequacy of resources benefit from the use of advanced spatial analysis tools. In order to provide better police service, it is necessary to divide the territory into areas or contiguous geographic clusters, which criteria may be having the same population, a similar crime rate, or balanced agent workloads. The process of grouping small geographic areas in service areas is called districting or zone design. The main objective of this work is the spatial optimization of the distribution of security forces considering the spatial disposition of the population in Setubal administrative district. In this paper, a genetic algorithm metaheuristic that addresses the police redistricting problem is proposed. The process of grouping areas into service areas was subject to constraints of population equality, contiguity and compactness. Data analysis was done with the hot spot analysis to study the population and their distribution at freguesia level. A genetic algorithm was implemented to create service areas (also known r-districs) and experimental analyses were performed with the population data and vulnerable groups. The simulations were made on 55 freguesias for 28 service areas. We compared the results with the Automatic Zoning Procedure - Simulated Annealing (AZP-SA). The population concentrates in Setubal peninsula, denoting a great asymmetry on their geographical distribution. Experimental tests with the genetic algorithm show a large variation of a sum of the population differences in service areas. Genetic algorithm presented on average 30402 inhabitants per service area. In the other hand, AZP-SA average was 29980. As regards the group with more than 65 years, both algorithms present on average 5599 inhabitants. The lowest compactness values were obtained with AZPSA in all tests performed. The absence of disaggregated data such as the number of crimes, geographical position of criminal incidents, the number of agents in the service, the number of cars per district were found as a drawback in our analysis. However, it is possible to simulate districts only with population data. The difficulty to obtain equitable areas is due to the great asymmetry of the population.
Descrição
Duarte, A., Henriques, R., & Ribeiro, S. (2019). Use of different optimization algorithms to define service areas of police stations in Portugal . In Evidence-based territorial policymaking: formulation, implementation and evaluation of policy: 26th APDR Congress Proceedings (pp. 108-115). Associacao Portuguesa para o Desenvolvimento Regional (APDR).
Palavras-chave
Police Stations Optimization Genetic Algorithms AZP-SA Service Areas Districting SDG 16 - Peace, Justice and Strong Institutions
Contexto Educativo
Citação
Editora
APDR - Associação Portuguesa para o Desenvolvimento Regional