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Stephan Beyer

Publications and source records attributed to Stephan Beyer.

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A Simple Primal-Dual Approximation Algorithm for 2-Edge-Connected Spanning Subgraphs

We propose a simple and natural approximation algorithm for the problem of finding a 2-edge-connected spanning subgraph of minimum total edge cost in a graph. The algorithm maintains a spanning forest starting with an empty edge set. In each iteration, a new edge incident to a leaf is selected in a natural greedy manner and added to the forest. If this produces a cycle, this cycle is contracted. This growing phase ends when the graph has been contracted into a single node and a subsequent cleanup step removes redundant edges in reverse order. We analyze the algorithm using the primal-dual method showing that its solution value is at most 3 times the optimum. Although this only matches the ratio of existing primal-dual algorithms, we require only a single growing phase, thereby addressing a question by Williamson. Also, we consider our algorithm to be not only conceptually simpler than the known approximation algorithms but also easier to implement in its entirety. For n and m being the number of nodes and edges, respectively, it runs in O(min{nm, m + n^2 log n}) time and O(m) space without data structures more sophisticated than binary heaps and graphs, and without graph algorithms beyond depth-first search.

cs.DS

Strong Steiner Tree Approximations in Practice

In this experimental study we consider Steiner tree approximations that guarantee a constant approximation of ratio smaller than $2$. The considered greedy algorithms and approaches based on linear programming involve the incorporation of $k$-restricted full components for some $k \geq 3$. For most of the algorithms, their strongest theoretical approximation bounds are only achieved for $k \to \infty$. However, the running time is also exponentially dependent on $k$, so only small $k$ are tractable in practice. We investigate different implementation aspects and parameter choices that finally allow us to construct algorithms (somewhat) feasible for practical use. We compare the algorithms against each other, to an exact LP-based algorithm, and to fast and simple $2$-approximations.

cs.DS