A stochastic optimization framework for resource management and course of action analysis

Michael J. Hirsch, Rakesh Nagi, David Sudit

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider a Course of Action (COA) problem domain with the support of information fusion technologies. We assume that level 1 and 2 fusion technologies have provided a set of suspicious/abnormal situations currently occurring and associated 'objects of interest' participating in these situations, along with likelihoods of participation. We further assume that there are limited resources available to gather additional information on these objects of interest. COA analysis and Resource Management (RM) prescribe placement of resources to accomplish desired information gathering tasks. Thus the goal of COA/RM is "putting the right resource in the right place and time to perform the appropriate information gathering task on the appropriate objects of interest." Our research focuses on formulating the COA/RM problem from a stochastic optimization framework, resulting in an NP-hard problem. An efficient heuristic is developed and demonstrated on an illustrative scenario from Maritime Domain Awareness.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th International Conference on Information Fusion, FUSION 2008
DOIs
StatePublished - 2008
Externally publishedYes
Event11th International Conference on Information Fusion, FUSION 2008 - Cologne, Germany
Duration: Jun 30 2008Jul 3 2008

Publication series

NameProceedings of the 11th International Conference on Information Fusion, FUSION 2008

Other

Other11th International Conference on Information Fusion, FUSION 2008
Country/TerritoryGermany
CityCologne
Period6/30/087/3/08

Keywords

  • Course of action
  • GRASP
  • Resource management
  • Stochastic optimization

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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