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A Formulation of Structural Design Optimization Problems for Quantum Annealing

Author

Listed:
  • Fabian Key

    (Institute of Lightweight Design and Structural Biomechanics (ILSB), TU Wien, Karlsplatz 13, A-1040 Vienna, Austria)

  • Lukas Freinberger

    (Institute of Lightweight Design and Structural Biomechanics (ILSB), TU Wien, Karlsplatz 13, A-1040 Vienna, Austria)

Abstract

We present a novel formulation of structural design optimization problems specifically tailored to be solved by qa. Structural design optimization aims to find the best, i.e., material-efficient yet high-performance, configuration of a structure. To this end, computational optimization strategies can be employed, where a recently evolving strategy based on quantum mechanical effects is qa. This approach requires the optimization problem to be present, e.g., as a qubo model. Thus, we develop a novel formulation of the optimization problem. The latter typically involves an analysis model for the component. Here, we use energy minimization principles that govern the behavior of structures under applied loads. This allows us to state the optimization problem as one overall minimization problem. Next, we map this to a qubo problem that can be immediately solved by qa. We validate the proposed approach using a size optimization problem of a compound rod under self-weight loading. To this end, we develop strategies to account for the limitations of currently available hardware. Remarkably, for small-scale problems, our approach showcases functionality on today’s hardware such that this study can lay the groundwork for continued exploration of qa’s impact on engineering design optimization problems.

Suggested Citation

  • Fabian Key & Lukas Freinberger, 2024. "A Formulation of Structural Design Optimization Problems for Quantum Annealing," Mathematics, MDPI, vol. 12(3), pages 1-18, February.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:3:p:482-:d:1332304
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    References listed on IDEAS

    as
    1. Kevin Wils & Boyang Chen, 2023. "A Symbolic Approach to Discrete Structural Optimization Using Quantum Annealing," Mathematics, MDPI, vol. 11(16), pages 1-29, August.
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