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Bounding the Greedy Strategy in Finite-Horizon String Optimization
We consider an optimization problem where the decision variable is a string
of bounded length. For some time there has been an interest in bounding the
performance of the greedy strategy for this problem. Here, we provide weakened
sufficient conditions for the greedy strategy to be bounded by a factor of
, where is the optimization horizon length. Specifically, we
introduce the notions of -submodularity and -GO-concavity, which together
are sufficient for this bound to hold. By introducing a notion of
\emph{curvature} , we prove an even tighter bound with the factor
. Finally, we illustrate the strength of our results by
considering two example applications. We show that our results provide weaker
conditions on parameter values in these applications than in previous results.Comment: This paper has been accepted by 2015 IEEE CD
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