Forced displacement has a huge impact on society today, asmore than 68million people are forcibly displaced worldwide. Existingmethods for forecasting the arrival of migrants, especially refugees, may help us to better allocate humanitarian support andprotection. However, few researchers have investigated the e ects of policy decisions, such as border closures, on the movement of these refugees. Recently established simulation development approaches have made it possible to conduct such a study. In this paper, we use such an approach to investigate the e ect of policy decisions on refugee arrivals for the South Sudan refugee crisis. To make such a study feasible in terms of human e ort, we rely on agent-based modelling, and have automated several phases of simulation development using the FabFlee automation toolkit. We observe a decrease in the average relative di erence from 0.615 to 0.499 as we improved the simulation model with additional information. Moreover, we conclude that the border closure and a reduction in camp capacity induce fewer refugee arrivals and more time spend travelling to other camps. While a border opening and an increase in camp capacity result in a limited increase in refugee arrivals at the destination camps. To the best of our knowledge, we are the first to conduct such an investigation for this conflict.

中文翻译：

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政策决策如何影响南苏丹的难民旅程：使用自动集合模拟的研究

当今，强迫流离失所对社会产生了巨大影响，全世界有超过6800万人被迫流离失所。预测移民特别是难民的到来的现有方法可能有助于我们更好地分配人道主义支持和保护。但是，很少有研究人员调查过有关这些难民流动的政策决定的效果，例如边界关闭。最近建立的仿真开发方法使进行这样的研究成为可能。在本文中，我们使用这种方法来调查有关针对南苏丹难民危机的难民到达的政策决定的效果。为了使这种研究在人的方面可行，我们依赖于基于代理的建模，并使用FabFlee自动化工具包实现了仿真开发的多个阶段的自动化。随着改进附加信息的仿真模型，我们发现平均相对差从0.615降低到0.499。此外，我们得出的结论是，边界关闭和营地容量的减少导致较少的难民到达，并花费更多的时间前往其他营地。边境开放和难民营容量的增加导致到达目的地难民营的难民人数有限。据我们所知，我们是第一个对这种冲突进行调查的人。边境开放和难民营容量的增加导致到达目的地难民营的难民人数有限。据我们所知，我们是第一个对这种冲突进行调查的人。边境开放和难民营容量的增加导致到达目的地难民营的难民人数有限。据我们所知，我们是第一个对这种冲突进行调查的人。