论文标题
多周期最大流量网络拦截
Multi-Period Max Flow Network Interdiction with Restructuring for Disrupting Domestic Sex Trafficking Networks
论文作者
论文摘要
我们考虑了一类新的多周期网络拦截问题,在整个时间范围内,在网络运行和实施网络之前,都会决定进行拦截和重组决策。我们讨论了如何将这个新问题应用于破坏家庭性贩运网络的方式,并引入了一种变种,其中第二个合作攻击者有能力阻止受害者并防止招募潜在受害者。该问题被建模为双光混合整数线性程序(BMILP),并使用列和构造生成求解,并使用部分信息解决。当网络运行之前实施所有插科时,我们还简化了BMILP。提出了基于建模的增强量,以显着改善大多数测试实例的解决方案时间。我们将我们的方法应用于综合家庭性贩运网络,并讨论我们模型的政策影响。特别是,我们展示了如何阻止潜在受害者的招募对于破坏性贩运与拘留现有参与者至关重要。
We consider a new class of multi-period network interdiction problems, where interdiction and restructuring decisions are decided upon before the network is operated and implemented throughout the time horizon. We discuss how we apply this new problem to disrupting domestic sex trafficking networks, and introduce a variant where a second cooperating attacker has the ability to interdict victims and prevent the recruitment of prospective victims. This problem is modeled as a bilevel mixed integer linear program (BMILP), and is solved using column-and-constraint generation with partial information. We also simplify the BMILP when all interdictions are implemented before the network is operated. Modeling-based augmentations are proposed to significantly improve the solution time in a majority of instances tested. We apply our method to synthetic domestic sex trafficking networks, and discuss policy implications from our model. In particular, we show how preventing the recruitment of prospective victims may be as essential to disrupting sex trafficking as interdicting existing participants.