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2007

Using Adaptive Priority Weighting to Direct Search in Probabilistic Scheduling

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Using Adaptive Priority Weighting to Direct Search in Probabilistic Scheduling
Many scheduling problems reside in uncertain and dynamic environments – tasks have a nonzero probability of failure and may need to be rescheduled. In these cases, an optimized solution for a short-term time horizon may have a detrimental impact over a broader time scale. We examine a scheduling domain in which time and energy on a phased array radar system is allocated to track objects in orbit around the earth. This domain requires probabilistic modeling to optimize the expected number of successful tasks on a particular day. Failed tasks must be attempted again on subsequent days. Given a set of task requests, we study two long-term objectives: percentage of requests initially successful, and the average time between successful request updates. We investigate adaptive priority weighting strategies that directly influence the short-term objective function and thus indirectly influence the long-term goals. We find that adapting priority weights based on when individual tasks suc...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where AIPS
Authors Andrew M. Sutton, Adele E. Howe, L. Darrell Whitley
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