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Computational Approaches to Max-Cut

In: Handbook on Semidefinite, Conic and Polynomial Optimization

Author

Listed:
  • Laura Palagi

    (Università degli Studi di Roma “La Sapienza”)

  • Veronica Piccialli

    (Università degli Studi di Roma Tor Vergata)

  • Franz Rendl

    (Alpen-Adria-Universität Klagenfurt)

  • Giovanni Rinaldi

    (Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”)

  • Angelika Wiegele

    (Alpen-Adria-Universität Klagenfurt)

Abstract

Max-Cut is one of the most studied combinatorial optimization problems because of its wide range of applications and because of its connections with other fields of discrete mathematics (see, e.g., the book by Deza and Laurent [10]). Like other interesting combinatorial optimization problems, Max-Cut is very simple to state.

Suggested Citation

  • Laura Palagi & Veronica Piccialli & Franz Rendl & Giovanni Rinaldi & Angelika Wiegele, 2012. "Computational Approaches to Max-Cut," International Series in Operations Research & Management Science, in: Miguel F. Anjos & Jean B. Lasserre (ed.), Handbook on Semidefinite, Conic and Polynomial Optimization, chapter 0, pages 821-847, Springer.
    • Handle: RePEc:spr:isochp:978-1-4614-0769-0_28
    DOI: 10.1007/978-1-4614-0769-0_28
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    Citations

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    Cited by:

    1. Christoph Buchheim & Emiliano Traversi, 2018. "Quadratic Combinatorial Optimization Using Separable Underestimators," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 424-437, August.
    2. Timotej Hrga & Janez Povh, 2021. "MADAM: a parallel exact solver for max-cut based on semidefinite programming and ADMM," Computational Optimization and Applications, Springer, vol. 80(2), pages 347-375, November.
    3. Weber, Shlomo & Castaneda Dower, Paul & Gokmen, Gunes & Le Breton, Michel, 2021. "Did the Cold War Produce Development Clusters in Africa?," CEPR Discussion Papers 15810, C.E.P.R. Discussion Papers.
    4. Christoph Buchheim & Marianna De Santis & Laura Palagi & Mauro Piacentini, 2012. "An Exact Algorithm for Quadratic Integer Minimization using Nonconvex Relaxations," DIS Technical Reports 2012-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".

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