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Preprint 631-1999

Combinatorial Optimization & Graph Algorithms group (COGA-Preprints)

Implementing Weighted b-Matching Algorithms: Insights from a Computational Study
extended abstract in Proceedings of the Workshop on Algorithm Engineering and Experimentation (ALENEX99), Baltimore, Maryland, USA, Lecture Notes in Computer Science, vol. 1619, pp. 18-36, Springer-Verlag
primary: 90C27 Combinatorial optimization
secondary: 90C35 Programming involving graphs or networks
weighted perfect b-matching, blossom algorithm, experimental study
We present an experimental study of an implementation of weighted perfect b-matching based on Pulleyblank's algorithm (1973). Although this problem is well-understood in theory and efficient algorithms are known, only little experience with implementations is available. In this paper several algorithmic variants are compared on synthetic and application problem data of very sparse graphs. This study was motivated by the practical need for an efficient b-matching solver for an industrial application, namely as a subroutine in our approach to a mesh refinement problem in computer-aided design (CAD).
Linear regression and operation counting is used to analyze code variants. The experiments indicate that a fractional jump-start should be used, a priority queue within the dual update helps, scaling of b-values is not necessary, whereas a delayed blossom shrinking heuristic significantly improves running times only for graphs with average degree two. The fastest variant of our implementation appears to be highly superior to a code by Miller and Pekny (1995).
The report may be requested from our secretary Gabriele Klink, email: klink@math.tu-berlin.de
Title: Source

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