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On a nonconvex MINLP formulation of the Euclidean Steiner tree problem in n-space: missing proofs

Abstract

We supply proofs for a few key results concerning smoothing square roots and model strengthening for a mixed-integer nonlinear-optimization formulation of the the Euclidean Steiner tree problem.

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Notes

  1. 1.

    See D’Ambrosio et al. [1].

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    D’Ambrosio, C., Fampa, M., Lee, J., Vigerske, S.: On a nonconvex MINLP formulation of the Euclidean Steiner Tree Problem in n-space. In: Bampis, E. (ed.) Experimental Algorithms, LNCS, vol. 9125. Springer, pp. 122–133 (2015)

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Acknowledgements

J. Lee was partially supported by NSF Grant CMMI-1160915 and ONR Grant N00014-14-1-0315, and Laboratoire d’Informatique de l’École Polytechnique. M. Fampa was partially supported by CNPq and FAPERJ.

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Correspondence to Jon Lee.

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D’Ambrosio, C., Fampa, M., Lee, J. et al. On a nonconvex MINLP formulation of the Euclidean Steiner tree problem in n-space: missing proofs. Optim Lett 14, 409–415 (2020). https://doi.org/10.1007/s11590-018-1295-1

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Keywords

  • Euclidean Steiner tree problem
  • Smoothing
  • Relaxation
  • Mixed-integer nonlinear optimization