Context-Aware Dynamic Asset Allocation for Maritime Interdiction Operations
IEEE Transactions on Systems, Man, and Cybernetics(2020)
摘要
This paper validates two approximate dynamic programming approaches on a maritime interdiction problem involving the allocation of
multiple
heterogeneous assets over a large area of responsibility to interdict
multiple
drug smugglers using
heterogeneous
types of transportation on the sea with varying contraband weights. The asset allocation is based on a probability of activity surface, which represents spatio-temporal target activity obtained by integrating intelligence data on drug smuggler whereabouts/waypoints for contraband transportation, behavior models, and meteorological and oceanographic information. We validate the proposed architectural and algorithmic concepts via several realistic mission scenarios. We conduct sensitivity analyses to quantify the robustness and proactivity of our approach, as well as to measure the value of information used in the allocation process. The contributions of this paper have been transitioned to and are currently being tested by Joint Interagency Task Force—South, an organization tasked with providing the initial line of defense against drug trafficking in the East Pacific and Caribbean Oceans.
更多查看译文
关键词
Resource management,Dynamic programming,Drugs,Stochastic processes,Transportation,Algorithm design and analysis,Planning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要