Application of QUBO solver using black-box optimization to structural design for resonance avoidance

Abstract

Quadratic unconstrained binary optimization (QUBO) solvers can be applied to design an optimal structure to avoid resonance. QUBO algorithms that work on a classical or quantum device have succeeded in some industrial applications. However, their applications are still limited due to the difficulty of transforming from the original optimization problem to QUBO. Recently, black-box optimization (BBO) methods have been proposed to tackle this issue using a machine learning technique and a Bayesian treatment for combinatorial optimization. We employed the BBO methods to design a printed circuit board for resonance avoidance. This design problem is formulated to maximize natural frequency and simultaneously minimize the number of mounting points. The natural frequency, which is the bottleneck for the QUBO formulation, is approximated to a quadratic model in the BBO method. We demonstrated that BBO using a factorization machine shows good performance in both the calculation time and the success probability of finding the optimal solution. Our results can open up QUBO solvers' potential for other applications in structural designs.

arXiv commentThis is a preprint of an article published in Scientific Reports. The final authenticated version is available online at: 10.1038/s41598-022-16149-8

References in corpus (16)

• Ising formulations of many NP problems
• Quantum Annealing in the Transverse Ising Model
• Quantum Annealing and Analog Quantum Computation
• Quantum Annealing for Industry Applications: Introduction and Review
• Expanding the horizon of automated metamaterials discovery via quantum annealing
• Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer
• Traffic Signal Optimization on a Square Lattice with Quantum Annealing
• Domain wall encoding of discrete variables for quantum annealing and QAOA
• Bayesian Optimization of Combinatorial Structures
• Convergence theorems for quantum annealing
• Machine Learning Framework for Quantum Sampling of Highly-Constrained, Continuous Optimization Problems
• Benchmark test of Black-box optimization using D-Wave quantum annealer
• Hybrid Quantum Annealing via Molecular Dynamics
• Tackling the challenge of a huge materials science search space with quantum-inspired annealing
• Continuous black-box optimization with quantum annealing and random subspace coding
• Combinatorial Black-box Optimization for Vehicle Design Problem

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