Approximation algorithms for Node-weighted Steiner Problems: Digraphs with Additive Prizes and Graphs with Submodular Prizes
November 07, 2022 Β· Declared Dead Β· π arXiv.org
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Authors
Gianlorenzo D'Angelo, Esmaeil Delfaraz
arXiv ID
2211.03653
Category
cs.DS: Data Structures & Algorithms
Cross-listed
cs.CC
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In the \emph{budgeted rooted node-weighted Steiner tree} problem, we are given a graph $G$ with $n$ nodes, a predefined node $r$, two weights associated to each node modelling costs and prizes. The aim is to find a tree in $G$ rooted at $r$ such that the total cost of its nodes is at most a given budget $B$ and the total prize is maximized. In the \emph{quota rooted node-weighted Steiner tree} problem, we are given a real-valued quota $Q$, instead of the budget, and we aim at minimizing the cost of a tree rooted at $r$ whose overall prize is at least $Q$. For the case of directed graphs with additive prize function, we develop a technique resorting on a standard flow-based linear programming relaxation to compute a tree with good trade-off between prize and cost, which allows us to provide very simple polynomial time approximation algorithms for both the budgeted and the quota problems. For the \emph{budgeted} problem, our algorithm achieves a bicriteria $(1+Ξ΅, O(\frac{1}{Ξ΅^2}n^{2/3}\ln{n}))$-approximation, for any $Ξ΅\in (0, 1]$. For the \emph{quota} problem, our algorithm guarantees a bicriteria approximation factor of $(2, O(n^{2/3}\ln{n}))$. Next, by using the flow-based LP, we provide a surprisingly simple polynomial time $O((1+Ξ΅)\sqrt{n} \ln {n})$-approximation algorithm for the node-weighted version of the directed Steiner tree problem, for any $Ξ΅>0$. For the case of undirected graphs with monotone submodular prize functions over subsets of nodes, we provide a polynomial time $O(\frac{1}{Ξ΅^3}\sqrt{n}\log{n})$-approximation algorithm for the budgeted problem that violates the budget constraint by a factor of at most $1+Ξ΅$, for any $Ξ΅\in (0, 1]$. Our technique allows us to provide a good approximation also for the quota problem.
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