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| Auteur principal: | |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2405.17676 |
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| _version_ | 1866916262780600320 |
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| author | Ayodele, Mayowa |
| author_facet | Ayodele, Mayowa |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_17676 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Utilising a Quantum Hybrid Solver for Bi-objective Quadratic Assignment Problems Ayodele, Mayowa Quantum Physics Artificial Intelligence G.1.6 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. |
| title | Utilising a Quantum Hybrid Solver for Bi-objective Quadratic Assignment Problems |
| topic | Quantum Physics Artificial Intelligence G.1.6 |
| url | https://arxiv.org/abs/2405.17676 |