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The Complexity and Approximability of Minimum Contamination Problems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6648))

Abstract

In this article, we investigate the complexity and approximability of the Minimum Contamination Problems, which are derived from epidemic spreading areas and have been extensively studied recently. We show that both the Minimum Average Contamination Problem and the Minimum Worst Contamination Problem are NP-hard problems even on restrict cases. For any ε> 0, we give \((1+\epsilon, O(\frac{1+\epsilon}{\epsilon}\log n))\)-bicriteria approximation algorithm for the Minimum Average Contamination Problem. Moreover, we show that the Minimum Average Contamination Problem is NP-hard to be approximated within 5/3 − ε and the Minimum Worst Contamination Problem is NP-hard to be approximated within 2 − ε, for any ε> 0, giving the first hardness results of approximation of constant ratios to the problems.

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Li, A., Tang, L. (2011). The Complexity and Approximability of Minimum Contamination Problems. In: Ogihara, M., Tarui, J. (eds) Theory and Applications of Models of Computation. TAMC 2011. Lecture Notes in Computer Science, vol 6648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20877-5_30

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  • DOI: https://doi.org/10.1007/978-3-642-20877-5_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20876-8

  • Online ISBN: 978-3-642-20877-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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