Simulation optimisation for the housing of homeless populations.

世界各地的政府机构负责住房，确保无家可归者不会长期无人庇护，并从长远来看能够获得高质量的住房。为此，它们必须在有限的预算范围内平衡对紧急住房的紧急需求和对永久性住房的长期需要。通过政府无家可归者护理系统的人流可以模拟为排队。由于这种排队系统的复杂性，模拟建模在估计住房发展计划的社会影响方面起着至关重要的作用。仿真模型善于捕捉现实世界系统的复杂性，但使用它们来找到最优开发计划是困难的。该项目旨在使用新颖的模拟优化算法，在无家可归者护理系统的背景下找到接近最佳的发展计划。这些算法将使用队列动力学的数学描述以及仿真模型来有效地探索不同的开发选项。模拟模型将依赖于对未来无家可归者的预测，这是高度不确定的。这里的挑战是适当地考虑这种不确定性对模拟输出和优化结果的影响。另一个挑战是，住房开发计划通常会被重新审视——在模拟优化的背景下考虑这一点将是一个新的发展。与美国蒙特利海军研究生院合作。

Government bodies around the world are responsible for housing which ensures that homeless people are not left unsheltered for extended periods of time and have access to good quality accommodation in the long run. To do this, they must balance the urgent requirements for emergency shelter with the long-term need for permanent housing, all within a limited budget. The flow of people through government homeless care systems can be modelled as a queue. Due to the complex nature of such queueing systems, simulation modelling plays a vital role in estimating the societal impact of housing development plans. Simulation models are good at capturing the complexities of the real-world system but using them to find an optimal development plan is difficult. This project aims to use novel simulation optimisation algorithms to find near-optimal development plans in the context of homeless care systems. These algorithms will use a mathematical description of the queue dynamics alongside a simulation model to efficiently explore different development options. The simulation model will rely on forecasts for future homelessness which are highly uncertain. The challenge here is to appropriately consider the impact of this uncertainty on the simulation output and on the optimisation results. A further challenge is the fact that housing development plans are typically revisited - to account for this in the context of simulation optimisation will be a novel development.In partnership with the Naval Postgraduate School, Monterey, US.