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.
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Acknowledgements
This work has been supported by the BMBF project ENets and the DFG projects GO 1920/4-1, HE 5386/15-1.
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Göttlich, S., Hameister, K., Herty, M. (2020). Convex Quadratic Mixed-Integer Problems with Quadratic Constraints. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds) Operations Research Proceedings 2019. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-48439-2_15
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