A General Data Reduction Scheme for Domination in Graphs
Data reduction by polynomial-time preprocessing is a core concept of (parameterized) complexity analysis in solving NP-hard problems. Its practical usefulness is confirmed by experimental work. Here, generalizing and extending previous work, we present a set of data reduction preprocessing rules on the way to compute optimal dominating sets in graphs. In this way, we arrive at the novel notion of “data reduction schemes.” In addition, we obtain data reduction results for domination in directed graphs that allow to prove a linear-size problem kernel for Directed Dominating Set in planar graphs.
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- 1.Aarts, E., Lenstra, J.K. (eds.): Local Search in Combinatorial Optimization. Wiley-Interscience Series in Discrete Mathematics and Optimization (1997)Google Scholar
- 2.Alber, J., Betzler, N., Niedermeier, R.: Experiments on Data Reduction for Optimal Domination in Networks. To appear, Annals of Operations Research (2005)Google Scholar
- 6.Dorn, B.: Extended Data Reduction Rules for Domination in Graphs (in German). Student Project, WSI für Informatik, Universität Tübingen, Germany (2004)Google Scholar