ISN2: Disrupting Human Trafficking via Needs Matching and Capacity Expansion

该奖项将通过研究如何随着时间的推移有效分配资源以破坏人口贩运网络，为促进国家健康、繁荣和福利做出贡献。阻止人口贩运的一个关键手段是通过更好地了解住房在个人脆弱性中所起的关键作用来减少潜在受害者的供应，这一点在很大程度上没有得到充分的研究。为了减少面临被贩运(或再被贩运)风险的人口，该项目提供了一项基于需求的纽约市无家可归青年流行率估计，以及一种基于优化的方法，以确定如何最有效地利用稀缺的住所和服务资源。庇护所和相关的康复服务通过减少人口贩运风险人群未来的脆弱性和累犯率，扰乱了人口贩运网络。这项奖励将通过制定部署边缘临时住房和服务能力的最佳政策，帮助指导一种长期、具有成本效益的干预方法。项目小组的跨学科和协作性质确保了这项研究的结果将产生实际影响，并在更广泛的反人口贩运研究界广泛传播。该项目为运筹学、数据科学和犯罪学的不同博士生团队提供了一个共同努力解决紧迫的社会问题的机会。该奖项将支持一种混合方法的研究方法，既涉及数据收集，又涉及分析模型制定，以分析减少潜在人口贩运受害者供应所需的能力。该项目将采用一种创新的捕获-重新捕获抽样战略，以了解在住房不稳定、贩运风险高的青年群体中庇护的重要性。该项目将与其服务提供商提供的数据一起，建立对弱势群体集体需求的基线评估。在此需求评估的基础上，提出了一个多维背包问题，该问题考虑了随时间变化的容量扩展和分配，并考虑了随机到达和停留时间。该项目确定了有限避难所能力的边际部署，以优化社会收益与成本比。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award will contribute to the advancement of national health, prosperity and welfare by studying the efficient allocation of resources over time to disrupt human trafficking networks. A key, and largely understudied, means to disrupt human trafficking is by reducing the supply of potential victims through a better understanding of the critical role that housing plays in individual vulnerability. In order to reduce the population at risk of being trafficked (or re-trafficked), this project provides a need-based prevalence estimation of homeless youth in New York City and an optimization-based approach to determine the most efficient use of scarce shelter and service resources. Shelter and associated rehabilitative services disrupt human trafficking networks by decreasing future vulnerability and recidivism for those at-risk of trafficking. This award will help guide a long-term, cost-effective intervention approach by developing an optimal policy for deployment of marginal temporal housing and services capacity. The interdisciplinary and collaborative nature of the project team ensures that the results of this research will have a practical impact and be disseminated widely within the broader anti-human trafficking research community. The project provides an opportunity for a diverse team of doctoral students in operations research, data science, and criminology to work together on a pressing societal problem. This award will support a mixed-methods research approach that involves both data collection and analytical model formulation to analyze capacity needed to reduce the supply of potential human trafficking victims. The project will employ an innovative capture-recapture sampling strategy to understand the importance of shelter in a population of unstably housed youth at high risk for trafficking. Together with data from their service providers, the project will establish a baseline assessment of the collective needs of vulnerable populations. With this needs assessment, a multiple multidimensional knapsack problem is formulated that allows for time-dependent capacity expansion and allocation and incorporates stochastic arrivals and length of stay. The project determines the marginal deployment of limited shelter capacity to optimize the societal benefit-to-cost ratio.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.