论文标题
一个决策支持系统，用于优化社会距离的成本，以便停止Covid-19的传播
A decision support system for optimizing the cost of social distancing in order to stop the spread of COVID-19
论文作者
论文摘要
目前，世界各地都有许多尝试使用计算机，智能手机，平板电脑和其他电子设备来停止Covid-19的传播。这些尝试中的大多数都集中在收集有关感染者的信息，以帮助健康的人避免与他们接触。但是，政府仍在经验上做出社会疏远决定。也就是说，当局没有自动化工具可以推荐要做出的决定，以最大程度地提高社会距离并最大程度地减少对经济的影响。在本文中，我们解决了上述问题，并设计了一种算法，该算法提供了有效的社会疏远方法（即，哪些学校，商店，工厂等）是有效的（即有助于减少病毒传播）并对经济产生较低影响的算法。简而言之：a）我们提出了几个模型（即组合优化问题）； b）我们对配方问题的计算复杂性显示了一些理论结果； c）我们为先前配制的问题中最复杂的问题提供了一种算法； d）我们实施和测试算法； e）我们为我们的问题展示了整数线性程序公式。
Currently there are many attempts around the world to use computers, smartphones, tablets and other electronic devices in order to stop the spread of COVID-19. Most of these attempts focus on collecting information about infected people, in order to help healthy people avoid contact with them. However, social distancing decisions are still taken by the governments empirically. That is, the authorities do not have an automated tool to recommend which decisions to make in order to maximize social distancing and to minimize the impact for the economy. In this paper we address the aforementioned problem and we design an algorithm that provides social distancing methods (i.e., what schools, shops, factories, etc. to close) that are efficient (i.e., that help reduce the spread of the virus) and have low impact on the economy. On short: a) we propose several models (i.e., combinatorial optimization problems); b) we show some theoretical results regarding the computational complexity of the formulated problems; c) we give an algorithm for the most complex of the previously formulated problems; d) we implement and test our algorithm; and e) we show an integer linear program formulation for our problem.
