Quick Navigation

Topics

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.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #67223 #67338 Provably Quantum-Secure Microgr... #67328 Faster and Better Quantum Softw... #67313 Digitized Counterdiabatic Quant... #67310 Women for Quantum -- Manifesto ...

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.