控制有向网络扩展过程的凸框架

V. Preciado, Michael Zargham, David Sun
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引用次数: 11

摘要

我们提出了一个凸优化框架来计算保护资源的最优分配,以控制在接触网络中传播的扩散过程。考虑的传播过程是流行的SIS模型在具有非相同节点和有向边的网络中的病毒感染的扩展。我们假设我们有有限的预算可以投资于三种类型的网络保护资源:(i)边缘控制资源,(ii),预防资源和(iii)纠正资源。利用边缘控制资源对接触网络中有向边的接触率进行限制。将预防性资源分配给节点,以减少该节点的感染概率(例如疫苗),将纠正性资源分配给节点,以提高该节点的回收率(例如解毒剂)。我们假设这些资源有与之相关的货币成本,由此我们形式化了一个最优预算分配问题,该问题最大限度地控制了感染。针对任意加权有向接触网络和一大类资源成本函数,利用几何规划(GP)给出了最优预算分配问题的多项式时间解。我们用实际航空运输网络的数值模拟来说明我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A convex framework to control spreading processes in directed networks
We propose a convex optimization framework to compute the optimal distribution of protection resources in order to control a spreading process propagating throughout a network of contacts. The spreading process under consideration is an extension of the popular SIS model of viral infection in a network with non-identical nodes and directed edges. We assume we have a limited budget available to invest on three types of network protection resources: (i) Edge control resources, (ii), preventative resources and (iii) corrective resources. Edge control resources are employed to impose restrictions on the contact rates across directed edges in the contact network. Preventative resources are allocated to nodes in order to reduce the probability of infection at that node (e.g. vaccines), and corrective resources are allocated to nodes to increase the recovery rate at that node (e.g. antidotes). We assume these resources have monetary costs associated with them, from which we formalize an optimal budget allocation problem which maximizes containment of the infection. We present a polynomial time solution to the optimal budget allocation problem using Geometric Programming (GP) for an arbitrary weighted and directed contact network and a large class of resource cost functions. We illustrate our approach with numerical simulations in a real-world air transportation network.
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