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A Continuous-Time Markov Decision Process for Infrastructure Surveillance

In: Operations Research Proceedings 2010

Author

Listed:
  • Jonathan Ott

    (Karlsruhe Institute of Technology)

Abstract

We consider the dynamics of threat of an infrastructure consisting of various sectors. The dynamics are modelled by a continuous-time Markov decision process (CMDP). A key property of the model is that dependencies between sectors are taken into account. The actions are determined by the number of the available security staff. The decision maker has to allocate the security staff to the sectors which leads to a resource allocation problem. The CMDP criterion is to minimize expected discounted total cost over an infinite horizon. This problem is computable only for very small infrastructures. To solve the problem for larger infrastructures, an index for a specific restless bandit model is introduced. The index can be easily implemented. The index is used as a basis of a heuristics which defines a sub-optimal decision rule for the surveillance task. By using this heuristics, memory requirements are reduced in order to store the suboptimal decision rule efficiently.

Suggested Citation

  • Jonathan Ott, 2011. "A Continuous-Time Markov Decision Process for Infrastructure Surveillance," Operations Research Proceedings, in: Bo Hu & Karl Morasch & Stefan Pickl & Markus Siegle (ed.), Operations Research Proceedings 2010, pages 327-332, Springer.
    • Handle: RePEc:spr:oprchp:978-3-642-20009-0_52
    DOI: 10.1007/978-3-642-20009-0_52
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