Abstract
We first propose a new method, called “bottom-up method”, that, informally, “propagates” improvement of the worst-case complexity for “sparse” instances to “denser” ones and we show an easy though non-trivial application of it to the min set cover problem. We then tackle max independent set. Following the bottom-up method we propagate improvements of worst-case complexity from graphs of average degree d to graphs of average degree greater than d. Indeed, using algorithms for max independent set in graphs of average degree 3, we tackle max independent set in graphs of average degree 4, 5 and 6. Then, we combine the bottom-up technique with measure and conquer techniques to get improved running times for graphs of maximum degree 4, 5 and 6 but also for general graphs. The best computation bounds obtained for max independent set are O *(1.1571n), O *(1.1918n) and O *(1.2071n), for graphs of maximum (or more generally average) degree 4, 5 and 6 respectively, and O *(1.2127n) for general graphs. These results improve upon the best known polynomial space results for these cases.
Research supported by the French Agency for Research under the DEFIS program TODO, ANR-09-EMER-010.
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Bourgeois, N., Escoffier, B., Paschos, V.T., van Rooij, J.M.M. (2010). A Bottom-Up Method and Fast Algorithms for max independent set . In: Kaplan, H. (eds) Algorithm Theory - SWAT 2010. SWAT 2010. Lecture Notes in Computer Science, vol 6139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13731-0_7
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DOI: https://doi.org/10.1007/978-3-642-13731-0_7
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