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Auteur principal: Ayodele, Mayowa
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:https://arxiv.org/abs/2405.17676
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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