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Continuous Approaches for Solving Discrete Optimization Problems

In: Handbook on Modelling for Discrete Optimization

Author

Listed:
  • Panos M Pardalos

    (University of Florida)

  • Oleg A Prokopyev

    (University of Florida)

  • Stanislav Busygin

    (University of Florida)

Abstract

This chapter contains short expository notes on applying continuous approaches for solving discrete optimization problems. We discuss some general aspects of the connection between integer programming and continuous optimization problems, along with several specific examples. The considered problems include maximum clique, satisfiability, the Steiner tree problem, minimax and semidefinite programming.

Suggested Citation

  • Panos M Pardalos & Oleg A Prokopyev & Stanislav Busygin, 2006. "Continuous Approaches for Solving Discrete Optimization Problems," International Series in Operations Research & Management Science, in: Gautam Appa & Leonidas Pitsoulis & H. Paul Williams (ed.), Handbook on Modelling for Discrete Optimization, chapter 0, pages 39-60, Springer.
    • Handle: RePEc:spr:isochp:978-0-387-32942-0_2
    DOI: 10.1007/0-387-32942-0_2
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    Citations

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    Cited by:

    1. Sašo Karakatič, 2020. "EvoPreprocess—Data Preprocessing Framework with Nature-Inspired Optimization Algorithms," Mathematics, MDPI, vol. 8(6), pages 1-29, June.
    2. Stefano Lucidi & Francesco Rinaldi, 2010. "An Exact Penalty Global Optimization Approach for Mixed-Integer Programming Problems," DIS Technical Reports 2010-17, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    3. Gili Rosenberg & Mohammad Vazifeh & Brad Woods & Eldad Haber, 2016. "Building an iterative heuristic solver for a quantum annealer," Computational Optimization and Applications, Springer, vol. 65(3), pages 845-869, December.
    4. Ma, Cheng & Zhang, Liansheng, 2015. "On an exact penalty function method for nonlinear mixed discrete programming problems and its applications in search engine advertising problems," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 642-656.
    5. Gary Kochenberger & Jin-Kao Hao & Fred Glover & Mark Lewis & Zhipeng Lü & Haibo Wang & Yang Wang, 2014. "The unconstrained binary quadratic programming problem: a survey," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 58-81, July.
    6. Stefano Lucidi & Francesco Rinaldi, 2009. "Exact Penalty Functions for Nonlinear Integer Programming Problems," DIS Technical Reports 2009-10, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    7. M. Santis & F. Rinaldi, 2012. "Continuous Reformulations for Zero–One Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 153(1), pages 75-84, April.
    8. Marianna De Santis & Francesco Rinaldi, 2010. "Continuous reformulations for zero-one programming problems," DIS Technical Reports 2010-16, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    9. Rupaj Kumar Nayak & Nirmalya Kumar Mohanty, 2020. "Solution of boolean quadratic programming problems by two augmented Lagrangian algorithms based on a continuous relaxation," Journal of Combinatorial Optimization, Springer, vol. 39(3), pages 792-825, April.
    10. S. Lucidi & F. Rinaldi, 2010. "Exact Penalty Functions for Nonlinear Integer Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 145(3), pages 479-488, June.

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