论文标题
基于Kruskal的多级坦者树问题的基于Kruskal的近似算法
Kruskal-based approximation algorithm for the multi-level Steiner tree problem
论文作者
论文摘要
我们研究了多层施泰纳树问题:在终端$ t $需要不同的优先级,级别或服务质量的图形中,施泰纳树问题的概括。在此问题中,我们试图找到一棵最低成本树,其中包含不同速率的边缘,以使任何两个端子$ u $,$ v $具有优先级$ p(u)$,$ p(v)$使用费率$ \ min \ min \ {p(u),p(v)\} $或更好的边缘连接。边缘成本与其速率成比例成正比的情况与最佳解决方案的恒定因素近似。对于更一般的非比例成本情况,与比率$ c \ log \ log n $相比,此问题很难大致,其中$ n $是图中的顶点数量。然而,Charikar等人的简单贪婪算法提供了$ \ min \ {2(\ ln | t | +1),在这种情况下\ ellρ\} $ - 在这种情况下近似,其中$ρ$是启发式的solver for steiner树问题和$ \ ell $ \ ell frk a的近似值(frive)的近似值。例如,$ρ\约1.39 $)。 在本文中,我们根据Kruskal的最小跨越树算法描述了对经典(单级)Steiner树近似算法的多层次概述的自然概括。我们证明,该算法的近似值至少与Charikar等人一样好,并且相对于最佳溶液的实验性能更好。我们开发了一个整数线性编程公式,以计算多层施泰纳树问题的精确解决方案,并使用非比例边缘成本,并使用它来评估我们在随机图和源自Steinlib的多层次实例上的性能。
We study the multi-level Steiner tree problem: a generalization of the Steiner tree problem in graphs where terminals $T$ require varying priority, level, or quality of service. In this problem, we seek to find a minimum cost tree containing edges of varying rates such that any two terminals $u$, $v$ with priorities $P(u)$, $P(v)$ are connected using edges of rate $\min\{P(u),P(v)\}$ or better. The case where edge costs are proportional to their rate is approximable to within a constant factor of the optimal solution. For the more general case of non-proportional costs, this problem is hard to approximate with ratio $c \log \log n$, where $n$ is the number of vertices in the graph. A simple greedy algorithm by Charikar et al., however, provides a $\min\{2(\ln |T|+1), \ell ρ\}$-approximation in this setting, where $ρ$ is an approximation ratio for a heuristic solver for the Steiner tree problem and $\ell$ is the number of priorities or levels (Byrka et al. give a Steiner tree algorithm with $ρ\approx 1.39$, for example). In this paper, we describe a natural generalization to the multi-level case of the classical (single-level) Steiner tree approximation algorithm based on Kruskal's minimum spanning tree algorithm. We prove that this algorithm achieves an approximation ratio at least as good as Charikar et al., and experimentally performs better with respect to the optimum solution. We develop an integer linear programming formulation to compute an exact solution for the multi-level Steiner tree problem with non-proportional edge costs and use it to evaluate the performance of our algorithm on both random graphs and multi-level instances derived from SteinLib.