Demand Modelling and Predictive Police Positioning for Effective Service Provision

在当今社会，经济压力意味着资源被压缩，有价值的服务的最终结果仍然是必要的。能够根据需要分配员工并充分利用这些资源对于企业的长期发展至关重要。对于紧急服务部门，特别是警察部门，要充分利用响应公众电话需求的资源，即当地警察，就需要最佳定位（地点设置），以促进反应，尽量减少到达事件的时间，尽量减少未能到达目标时间的风险，并尽量提高公众的能见度。这些地点需要反映此类需求电话的“热点”。为了更好地提供服务，并且需要让人们看到这些热点，这些热点需要是路线，而不是固定的点，这些热点会根据一天中的时间、一周中的一天和一年中的一个月而变化。与此同时，有关人员需要一些稳定性，以便能够实际管理他们的班次。在这项研究建议中，我们利用历史数据和预测模型工具，根据规定的警务人员需求，制定最佳策略来分配和安置人员。这将需要扩大设施定位方法，以便在不断变化和不确定的环境中处理实时、可变和静态定位。即将生成的建模工具将提供一种自动化机制，以产生最佳的警官位置定位，并能够促进固定和预测巡逻路线，从而在最短的时间内最大限度地满足需求。这种复杂程度目前在部队中是看不到的。警方若具备预测能力，并能作出最佳反应，便可减轻社会对警方在打击罪案方面的角色的恐惧。对犯罪的潜在影响是巨大的。

In today's society where economic pressures mean resources are being squeezed, the end outcome of a valued service is still necessary. Being able to allocate staff as required and making the best use of these resources is critical for the longevity of business. For the emergency services, in particular the Police Force, making the best use of the resources, namely the Local Police Officers, that respond to demand from calls from the public, requires optimal positioning (location setting) to facilitate the response minimizing time to reach the incident, minimizing the risk of failure to reach target arrival times and maximizing the visibility to the public. These locations need to reflect the 'hot spots' for such demand calls. For a more enhanced service provision and the need to be visible these hot spots need to be routes, rather than stationary points, which will vary depending on the time of day, day of the week and month of the year. At the same time the personnel involved need some stability in terms of being able to practically manage their shift. Within this research proposal, the use of historical data, as well as predictive modelling tools, are used to facilitate the best strategy to allocate and position staff based on the prescribed demand for Police Officers. This will require methods of facility location to be extended to deal with real time, variable and static positioning, in a changing and uncertain environment. The modelling tool to be generated will provide an automated mechanism to produce optimal Officer location positioning, with the ability to facilitate stationary and predictive patrol routes to maximize the ability to meet demand in the shortest amount of time. This level of sophistication is not currently seen within the force. For the Police to have the predictive capability coupled with the most optimal response serves to alleviate fears of society as to the role of Police with regards to crime. The potential impact on Crime is immense.