D-ISN: TRACK 1: Collaborative Research: Discovery, Analysis, and Disruption of Illicit Narcotic Supply Networks

随着跨国贩毒集团的规模和范围不断扩大，其贩运网络变得更加复杂和支离破碎。这一非法供应网络扰乱行动(D-ISN)项目采取了多学科的科学方法，以更好地洞察和优化美国的禁毒工作。它改进了分析方法，以发展对可卡因流动的网络结构和模型的理解，这为禁毒和其他执法机构的破坏战略提供支持。该项目分析了毒品供应网络的动态以及阻止战略如何破坏这些网络。本研究结合运筹学、计算机科学、犯罪学、公共政策、地理学和经济学等多学科的研究成果，运用时空可卡因价格数据的网络分析方法，推断出非法供应链的网络结构和流动。人工智能和学习模型被应用于经验数据，以提取响应于拦截活动的网络行为，而博弈论模型融合了组合优化和基于代理的模拟来评估各种拦截策略的结果。结果将被整合到网络优化模型中，以解释非法药物供应链的结构，并提供证据支持成功的破坏战略。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。

As transnational drug cartels continue to grow in size and scope, their trafficking networks have become more complex and fragmented. This Disrupting Operations of Illicit Supply Networks (D-ISN) project takes a multi-disciplinary, scientific approach to build better insight and optimization of counter-narcotics efforts in the United States. It refines analytic methods to develop an understanding of the network structure and models of the flow of cocaine, which supports disruption strategies of anti-narcotics and other law enforcement agencies.The project analyzes the dynamics of narcotic supply networks and how interdiction strategies disrupt these networks. Employing a convergent approach that combines operations research, computer science, criminology, public policy, geographic, and economic perspectives, this research exploits network analysis of temporal and spatial cocaine price data to infer illicit supply chain network structure and flow. Artificial intelligence and learning models are applied on the empirical data to extract network behavior in response to interdiction activities, while game theoretic models blend combinatorial optimization and agent-based simulation to evaluate the outcomes of various interdiction strategies. Results will be integrated into a network optimization model to explain the structure of illicit drug supply chains and provide evidence to support successful disruption strategies.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.