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Quantum Optimization
Quantum Machine Learning
Utilising a Quantum Hybrid Solver for Bi-objective Quadratic Assignment Problems
arXiv
Authors: Mayowa Ayodele
Year
2024
Paper ID
67223
Status
Preprint
Abstract Read
~2 min
Abstract Words
66
Citations
N/A
Abstract
The intersection between quantum computing and optimisation has been an area of interest in recent years. There have been numerous studies exploring the application of quantum and quantum-hybrid solvers to various optimisation problems. This work explores scalarisation methods within the context of solving the bi-objective quadratic assignment problem using a quantum-hybrid solver. We show results that are consistent with previous research on a different Ising machine.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- The intersection between quantum computing and optimisation has been an area of interest in recent years.
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