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Approximation Algorithms for Fragmenting a Graph against a Stochastically-Located Threat

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7164)

Abstract

Motivated by issues in allocating limited preventative resources to protect a landscape against the spread of a wildfire from a stochastic ignition point, we give approximation algorithms for a new family of stochastic optimization problems.

Keywords

  • Approximation Algorithm
  • Edge Cost
  • Fuel Treatment
  • Ignition Point
  • Stage Variable

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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  6. Shmoys, D., Spencer, G.: Full paper: Approximation algorithms for fragmenting a graph against a stochastically-located threat, http://people.orie.cornell.edu/gms39/images/documents/gsfragment.pdf

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Shmoys, D.B., Spencer, G. (2012). Approximation Algorithms for Fragmenting a Graph against a Stochastically-Located Threat. In: Solis-Oba, R., Persiano, G. (eds) Approximation and Online Algorithms. WAOA 2011. Lecture Notes in Computer Science, vol 7164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29116-6_11

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  • DOI: https://doi.org/10.1007/978-3-642-29116-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29115-9

  • Online ISBN: 978-3-642-29116-6

  • eBook Packages: Computer ScienceComputer Science (R0)