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Narrowing the Search for Optimal Call-Admission Policies Via a Nonlinear Stochastic Knapsack Model

Author

Listed:
  • Marco Cello

    (University of Genoa)

  • Giorgio Gnecco

    (Institute for Advanced Studies (IMT)
    University of Genoa)

  • Mario Marchese

    (University of Genoa)

  • Marcello Sanguineti

    (University of Genoa)

Abstract

Call admission control with two classes of users is investigated via a nonlinear stochastic knapsack model. The feasibility region represents the subset of the call space, where given constraints on the quality of service have to be satisfied. Admissible strategies are searched for within the class of coordinate-convex policies. Structural properties that the optimal policies belonging to such a class have to satisfy are derived. They are exploited to narrow the search for the optimal solution to the nonlinear stochastic knapsack problem that models call admission control. To illustrate the role played by these properties, the numbers of coordinate-convex policies by which they are satisfied are estimated. A graph-based algorithm to generate all such policies is presented.

Suggested Citation

  • Marco Cello & Giorgio Gnecco & Mario Marchese & Marcello Sanguineti, 2015. "Narrowing the Search for Optimal Call-Admission Policies Via a Nonlinear Stochastic Knapsack Model," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 819-841, March.
    • Handle: RePEc:spr:joptap:v:164:y:2015:i:3:d:10.1007_s10957-014-0570-2
    DOI: 10.1007/s10957-014-0570-2
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    References listed on IDEAS

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