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Application of hybrid metaheuristics in sensor management
Institution:1. Thales Research & Technology NL, Delft Cooperation on Intelligent Systems, PO Box 90, 2600 AB Delft, The Netherlands;2. CAMS – Force Vision, MPC 10A, PO Box 10000, 1780 CA Den Helder, The Netherlands;1. Department of Statistics, University of Michigan, United States;2. Department of Electrical Engineering and Computer Science, University of Michigan, United States;1. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, United States;2. Remote Sensing Solutions, 248 E Foothill Blvd. Suite 200, Monrovia, CA 91016, United States;3. Applied Physics Laboratory, University of Washington, 1013 NE 40th St. Box 355640, Seattle, WA 98105, United States;1. 291 Daehak-ro, Division of Aerospace Engineering, KAIST, Yuseong, Daejeon 305-701, Republic of Korea;2. Bugyuseong-daero 488 beon-gil, Agency for Defense Development, Yuseong, Daejeon 305-152, Republic of Korea
Abstract:The capacity of today's sensor systems has rapidly grown beyond the borders of human controllability. The real time (re)scheduling that is needed to manage them can only be done using state of the art planning and scheduling methods. This paper discusses one of the most recent and promising advances in operations research and artificial intelligence planning systems: hybrid metaheuristics. These robust heuristic search techniques efficiently use limited time and computing resources to produce good schedules within short term. Simulations show the use and performance of these techniques in multi-function radar systems.
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