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Robust multi-sensor scheduling for multi-site surveillance

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Abstract

This paper presents mathematical programming techniques for solving a class of multi-sensor scheduling problems. Robust optimization problems are formulated for both deterministic and stochastic cases using linear 0–1 programming techniques. Equivalent formulations are developed in terms of cardinality constraints. We conducted numerical case studies and analyzed the performance of optimization solvers on the considered problem instances.

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Authors and Affiliations

  1. University of Florida, 303 Weil Hall, Gainesville, FL, 32611, USA

    Nikita Boyko, Timofey Turko, Stanislav Uryasev, Grigoriy Zrazhevsky & Panos M. Pardalos

  2. University of Florida REEF, 1350 N Poquito Road, Shalimar, FL, 32579, USA

    Vladimir Boginski

  3. Air Force Research Laboratory, 101 West Eglin Boulevard, Bldg. 13, Eglin Air Force Base, FL, 32542, USA

    David E. Jeffcoat

Authors
  1. Nikita Boyko
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  2. Timofey Turko
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  3. Vladimir Boginski
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  4. David E. Jeffcoat
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  5. Stanislav Uryasev
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  6. Grigoriy Zrazhevsky
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  7. Panos M. Pardalos
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Corresponding author

Correspondence to Nikita Boyko.

Additional information

The research was supported by AFOSR grants # 07MN01COR and FA9550-08-1- 0190 and Air Force contract # F08635-03-D-0130.

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Boyko, N., Turko, T., Boginski, V. et al. Robust multi-sensor scheduling for multi-site surveillance. J Comb Optim 22, 35–51 (2011). https://doi.org/10.1007/s10878-009-9271-4

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  • DOI: https://doi.org/10.1007/s10878-009-9271-4

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