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The unconstrained binary quadratic programming problem: a survey

Author

Listed:
  • Gary Kochenberger

    (University of Colorado at Denver)

  • Jin-Kao Hao

    (Université d’Angers)

  • Fred Glover

    (OptTek Inc.)

  • Mark Lewis

    (Missouri Western State University)

  • Zhipeng Lü

    (Huazhong University of Science and Technology)

  • Haibo Wang

    (Texas A&M International University)

  • Yang Wang

    (Northwestern Polytechnical University)

Abstract

In recent years the unconstrained binary quadratic program (UBQP) has grown in importance in the field of combinatorial optimization due to its application potential and its computational challenge. Research on UBQP has generated a wide range of solution techniques for this basic model that encompasses a rich collection of problem types. In this paper we survey the literature on this important model, providing an overview of the applications and solution methods.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jcomop:v:28:y:2014:i:1:d:10.1007_s10878-014-9734-0
    DOI: 10.1007/s10878-014-9734-0
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    23. Aufenanger, Tobias, 2018. "Treatment allocation for linear models," FAU Discussion Papers in Economics 14/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2018.

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