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Robust multi-sensor scheduling for multi-site surveillance

Author

Listed:
  • Nikita Boyko

    (University of Florida)

  • Timofey Turko

    (University of Florida)

  • Vladimir Boginski

    (University of Florida REEF)

  • David E. Jeffcoat

    (Air Force Research Laboratory)

  • Stanislav Uryasev

    (University of Florida)

  • Grigoriy Zrazhevsky

    (University of Florida)

  • Panos M. Pardalos

    (University of Florida)

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.

Suggested Citation

  • Nikita Boyko & Timofey Turko & Vladimir Boginski & David E. Jeffcoat & Stanislav Uryasev & Grigoriy Zrazhevsky & Panos M. Pardalos, 2011. "Robust multi-sensor scheduling for multi-site surveillance," Journal of Combinatorial Optimization, Springer, vol. 22(1), pages 35-51, July.
    • Handle: RePEc:spr:jcomop:v:22:y:2011:i:1:d:10.1007_s10878-009-9271-4
    DOI: 10.1007/s10878-009-9271-4
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    References listed on IDEAS

    as
    1. Miguel Lobo & Maryam Fazel & Stephen Boyd, 2007. "Portfolio optimization with linear and fixed transaction costs," Annals of Operations Research, Springer, vol. 152(1), pages 341-365, July.
    2. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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