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Convex Quadratic Mixed-Integer Problems with Quadratic Constraints

In: Operations Research Proceedings 2019

Author

Listed:
  • Simone Göttlich

    (Mannheim University)

  • Kathinka Hameister

    (Mannheim University)

  • Michael Herty

    (RWTH Aachen University)

Abstract

The efficient numerical treatment of convex quadratic mixed-integer optimization poses a challenging problem. Therefore, we introduce a method based on the duality principle for convex problems to derive suitable lower bounds that can used to select the next node to be solved within the branch-and-bound tree. Numerical results indicate that the new bounds allow the tree search to be evaluated quite efficiently compared to benchmark solvers.

Suggested Citation

  • Simone Göttlich & Kathinka Hameister & Michael Herty, 2020. "Convex Quadratic Mixed-Integer Problems with Quadratic Constraints," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 123-129, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-48439-2_15
    DOI: 10.1007/978-3-030-48439-2_15
    as

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