Bicriterial Approximation for the Incremental Prize-Collecting Steiner-Tree Problem

Yann Disser, Svenja M. Griesbach, Max Klimm, Annette Lutz
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Abstract

We consider an incremental variant of the rooted prize-collecting Steiner-tree problem with a growing budget constraint. While no incremental solution exists that simultaneously approximates the optimum for all budgets, we show that a bicriterial $(\alpha,\mu)$-approximation is possible, i.e., a solution that with budget $B+\alpha$ for all $B \in \mathbb{R}_{\geq 0}$ is a multiplicative $\mu$-approximation compared to the optimum solution with budget $B$. For the case that the underlying graph is a tree, we present a polynomial-time density-greedy algorithm that computes a $(\chi,1)$-approximation, where $\chi$ denotes the eccentricity of the root vertex in the underlying graph, and show that this is best possible. An adaptation of the density-greedy algorithm for general graphs is $(\gamma,2)$-competitive where $\gamma$ is the maximal length of a vertex-disjoint path starting in the root. While this algorithm does not run in polynomial time, it can be adapted to a $(\gamma,3)$-competitive algorithm that runs in polynomial time. We further devise a capacity-scaling algorithm that guarantees a $(3\chi,8)$-approximation and, more generally, a $\smash{\bigl((4\ell - 1)\chi, \frac{2^{\ell + 2}}{2^{\ell}-1}\bigr)}$-approximation for every fixed $\ell \in \mathbb{N}$.
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增量奖品收集斯坦纳树问题的双标准近似法
我们考虑了预算约束不断增长的有根奖收集斯泰纳树问题的增量变体。虽然不存在能同时逼近所有预算的最优解的增量解,但我们证明了双标准 $(\alpha,\mu)$逼近是可能的,也就是说,对于 \mathbb{R}_{geq 0}$ 中的所有 $B,预算为 $B+\alpha$ 的解与预算为 $B$ 的最优解相比,是一个乘法 $\mu$ 逼近解。对于底层图是一棵树的情况,我们提出了一种计算$(\chi,1)$近似值的多项式时间密度-贪婪算法,其中$\chi$表示底层图中根顶点的偏心率,并证明这是最佳可能的。针对一般图的密度-贪婪算法的适应性是$(\gamma,2)$竞争性的,其中$\gamma$是以根为起点的平均顶点相交路径的最大长度。虽然这种算法不能在多项式时间内运行,但它可以改编成一种在多项式时间内运行的 $(\gamma,3)$ 竞争性算法。我们进一步设计了一种容量缩放算法,它可以保证在\mathbb{N}$中的每一个固定$\ell \都有一个$(3\chi,8)$近似值,更广泛地说,还有一个$smash{bigl((4\ell - 1)\chi, \frac{2^{\ell +2}}{2^{\ell}-1}\bigr)}$ 近似值。
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