In this paper, we develop a new algorithm combining the idea of ``boosting'' with the first-order algorithm to approximately solve a class of (Integer) Linear programs(LPs) arisen in general resource allocation problems. Not only can this algorithm solve LPs directly, but also can be applied to accelerate the Column Generation method. As a direct solver, our algorithm achieves a provable $O(\sqrt{n/K})$ optimality gap, where $n$ is the number of variables and $K$ is the number of data duplication bearing the same intuition as the boosting algorithm. We use numerical experiments to demonstrate the effectiveness of our algorithm and several variants.
翻译：在本文中,我们开发了一种新的算法,将“加速”的概念与第一级算法结合起来,以大致解决在一般资源分配问题中产生的一类( Integer)线性程序(LPs ) 。 这种算法不仅可以直接解决LPs,而且可以用于加速“列生成”方法。作为一个直接解决者,我们的算法实现了一个可被证实的$O(sqrt{n/K}) /$的最佳性差距,即零美元是变量的数量,而$Ks(K)是具有与增强算法相同直觉的数据重复数量。我们用数字实验来证明我们的算法和几种变式的有效性。
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