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On the State of QUBO Solving

In: Operations Research Proceedings 2023

Author

Listed:
  • Thorsten Koch

    (Zuse Institute Berlin
    Technische Universität Berlin)

  • Daniel Rehfeldt

    (Zuse Institute Berlin)

  • Yuji Shinano

    (Zuse Institute Berlin)

Abstract

It is regularly claimed that quantum computers will bring breakthrough progress in solving challenging combinatorial optimization problems relevant in practice. In particular, Quadratic Unconstrained Binary Optimization (QUBO) problems are said to be the model of choice for use in (adiabatic) quantum systems during the noisy intermediate-scale quantum (NISQ) era. Even the first commercial quantum-based systems are advertised to solve such problems. Theoretically, any Integer Program can be converted into a QUBO. In practice, however, there are some caveats, as even for problems that can be nicely modeled as a QUBO, this might not be the most effective way to solve them. We review the state of QUBO solving on digital and quantum computers and provide insights regarding current benchmark instances and modeling.

Suggested Citation

  • Thorsten Koch & Daniel Rehfeldt & Yuji Shinano, 2025. "On the State of QUBO Solving," Lecture Notes in Operations Research, in: Guido Voigt & Malte Fliedner & Knut Haase & Wolfgang Brüggemann & Kai Hoberg & Joern Meissner (ed.), Operations Research Proceedings 2023, chapter 0, pages 357-365, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-58405-3_46
    DOI: 10.1007/978-3-031-58405-3_46
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