146 research outputs found

    Bounding the Greedy Strategy in Finite-Horizon String Optimization

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    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 (1βˆ’(1βˆ’1/K)K)(1-(1-1/K)^K), where KK is the optimization horizon length. Specifically, we introduce the notions of KK-submodularity and KK-GO-concavity, which together are sufficient for this bound to hold. By introducing a notion of \emph{curvature} η∈(0,1]\eta\in(0,1], we prove an even tighter bound with the factor (1/Ξ·)(1βˆ’eβˆ’Ξ·)(1/\eta)(1-e^{-\eta}). 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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