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New primal-dual algorithms for Steiner tree problems

机译:Steiner树问题的新的对偶算法

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We present new primal-dual algorithms for several network design problems. The problems considered are the generalized Steiner tree problem (GST), the directed Steiner tree problem (DST), and the set cover problem (SC) which is a subcase of DST. All our problems are NP-hard; so we are interested in their approximation algorithms. First, we give an algorithm for DST which is based on the traditional approach of designing primal-dual approximation algorithms. We snow that the approximation factor of the algorithm is k, where k is the number of terminals, in the case when the problem is restricted to quasi-bipartite graphs. We also give pathologically bad examples for the algorithm performance. To overcome the problems exposed by the bad examples, we design a new framework for primal-dual algorithms which can be applied to all of our problems. The main feature of the new approach is that, unlike the traditional primal-dual algorithms, it keeps the dual solution in the interior of the dual feasible region. The new approach allows us to avoid including too many arcs in the solution, and thus achieves a smaller-cost solution. Our computational results show that the interior-point version of the primal-dual most of the time performs better than the original primal-dual method.
机译:我们针对几个网络设计问题提出了新的原始对偶算法。所考虑的问题是广义Steiner树问题(GST),有向Steiner树问题(DST)和DST的子情形集覆盖问题(SC)。我们所有的问题都是NP难题。所以我们对他们的近似算法很感兴趣。首先,我们给出了一种DST算法,该算法基于设计原始对偶近似算法的传统方法。我们下雪了,在问题仅限于拟二分图的情况下,该算法的近似因子为k,其中k为终端数。对于算法性能,我们还给出了病理上不好的例子。为了克服不良示例所暴露的问题,我们为原对偶算法设计了一个新框架,该框架可以应用于所有问题。新方法的主要特点是,与传统的原始对偶算法不同,它将对偶解保留在对偶可行域的内部。新方法使我们能够避免在解决方案中包含过多的弧,从而实现成本更低的解决方案。我们的计算结果表明,大多数情况下,原始双对偶的内点版本比原始原始双对偶方法的性能更好。

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