This paper presents an application of optimization and geographic information systems techniques for deploying police facilities subject to budgetary and feasibility constraints. The objectives include minimizing the distances and maximizing the coverage of police stations over potential crime spots. Two optimization models were investigated: maximum coverage and p-median problems. The optimization was integrated with geographic spatial analysis techniques to allocate limited police resources in the Greater London Area. In addition, the optimal results were compared with existing police deployment in London. Finally, the resilience of optimal solutions was evaluated by applying them to the scenario of the terrorist attack that occurred on July 7, 2005. This study contributes to the study of urban sustainability and security.
Purpose – This paper aims to present an application of location optimization techniques for deploying police facilities subject to budgetary and feasibility constraints. The objectives considered included minimizing the distances and maximizing the coverage of police stations over potential crime spots. Design/methodology/approach – The optimization consists of two stages. In Stage 1, a minimum distance model is used to determine the locations of police stations. Given the locations of police stations, Stage 2 uses a maximum coverage model to determine the police patrol area. The framework is applied to a case in the Greater London Area. The authors also evaluate the resilience of the optimal solutions with the terrorist attack scenario on 7 July 2005 in Central London. Findings – With the optimization models, it is shown that the average distance between police stations and potential crime spots is reduced by 19 per cent. The coverage percentage of potential crime spots is also increased from the existing 91.99 per cent to a nearly perfect 99.82 per cent. Nevertheless, the results reveal that the optimal police resources deployment is less resilient with respect to the existing one. The findings herein suggest the importance of incorporating measures of resilience into the optimization framework and the authors leave this topic for further investigation. Originality/value – The study highlights the value of location optimization to police force deployment in terms of finding the optimal locations of police force with respect to the spatial distribution of crimes. In particular, the authors investigate its implication on urban resilience, which is among the first study of this kind.
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