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.

生成讲解博客的中文版本

生成AI智能校验的中文版本