Optimization-based Algorithms for Context-Driven Proactive Decision Support and Planning in Dynamic and Uncertain Mission Environments
Digital Document
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Handle
http://hdl.handle.net/11134/20002:860653516
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Persons |
Persons
Creator (cre): Mishra, Manisha
Major Advisor (mja): Pattipati, Krishna R.
Associate Advisor (asa): Bar-Shalom, Yaakov
Associate Advisor (asa): Luh, Peter B.
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Title |
Title
Title
Optimization-based Algorithms for Context-Driven Proactive Decision Support and Planning in Dynamic and Uncertain Mission Environments
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Origin Information
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Parent Item
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Digital Origin |
Digital Origin
born digital
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Description |
Description
Future maritime battlespace environments are expected to be complex, distributed and network centric. Given our ability to collect massive amounts of data using heterogeneous sources, it is imperative to process the collected data and present relevant information to the decision makers (DMs) in a timely manner to make effective decisions under dynamic, uncertain and unpredictable mission scenarios (e.g., sudden changes in mission goals, environment, assets and mission tasks). In addition to data/information processing, it is crucial to dynamically allocate and route the scarce and expensive resources to maximize the amount of decision-relevant information collected, while increasing the probability of mission success. These challenges necessitate the development of a framework for the acquisition, fusion, and transfer of the right data/information/knowledge from the right sources in the right context to the right DM at the right time for the right purpose - a concept known as 6R. The research in this thesis seeks to develop and test algorithms for proactive decision making to extract, process, and integrate relevant information and improve dynamic resource management for mission planning and re-planning. We envision a proactive decision support framework for C4ISR (Command Control Communications Computers, Intelligence, Surveillance and Reconnaissance) planning process that dynamically invokes plans as a function of emerging events, readily adapts plans to meet unfolding events, monitors the outcomes of many of its previous decisions, and re-plans, if warranted, within the context of: 1) Antisubmarine Warfare (ASW) mission planning and generalized bounds on probability of target detection; 2) Multi-objective coordinated path planning for Unmanned Aerial Vehicles (UAVs); 3) Dynamic resource management for maritime mission planning; and 4) Distributed command and control architectures for efficient communication and workload balance in a network.
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Genre
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Organizations
Degree granting institution (dgg): University of Connecticut
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Rights Statement
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Use and Reproduction |
Use and Reproduction
These materials are provided for educational and research purposes only.
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Local Identifier |
Local Identifier
OC_d_1773
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