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Multivariate Complexity Analysis of Geometric Red Blue Set Cover

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We investigate the parameterized complexity of Generalized Red Blue Set Cover (Gen-RBSC), a generalization of the classic Set Cover problem and the more recently studied Red Blue Set Cover problem. Given a universe U containing b blue elements and r red elements, positive integers \(k_\ell \) and \(k_r\), and a family \(\mathcal F \) of \(\ell \) sets over U, the Gen-RBSC problem is to decide whether there is a subfamily \(\mathcal F '\subseteq \mathcal F \) of size at most \(k_\ell \) that covers all blue elements, but at most \(k_r\) of the red elements. This generalizes Set Cover and thus in full generality it is intractable in the parameterized setting. In this paper, we study a geometric version of this problem, called Gen-RBSC-lines, where the elements are points in the plane and sets are defined by lines. We study this problem for an array of parameters, namely, \(k_\ell , k_r, r, b\), and \(\ell \), and all possible combinations of them. For all these cases, we either prove that the problem is W-hard or show that the problem is fixed parameter tractable (FPT). In particular, on the algorithmic side, our study shows that a combination of \(k_\ell \) and \(k_r\) gives rise to a nontrivial algorithm for Gen-RBSC-lines. On the hardness side, we show that the problem is para-NP-hard when parameterized by \(k_r\), and W[1]-hard when parameterized by \(k_\ell \). Finally, for the combination of parameters for which Gen-RBSC-lines admits FPT algorithms, we ask for the existence of polynomial kernels. We are able to provide a complete kernelization dichotomy by either showing that the problem admits a polynomial kernel or that it does not contain a polynomial kernel unless \(\text {co{-}NP}\subseteq \text {NP}/\text{ poly }\).

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Acknowledgments

We would like to thank an anonymous reviewer who gave very insightful suggestions and in particular, the simple dynamic programming algorithm for a special case of Gen-RBSC.

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Correspondence to Sudeshna Kolay.

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The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement No. 306992.

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Ashok, P., Kolay, S. & Saurabh, S. Multivariate Complexity Analysis of Geometric Red Blue Set Cover . Algorithmica 79, 667–697 (2017). https://doi.org/10.1007/s00453-016-0216-x

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