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Quantum Optimization Quantum Machine Learning Quantum Simulation

Quantum walk-based vehicle routing optimisation

arXiv
Authors: Tavis Bennett, Edric Matwiejew, Sam Marsh, Jingbo B. Wang

Year

2021

Paper ID

61117

Status

Preprint

Abstract Read

~2 min

Abstract Words

93

Citations

N/A

Abstract

This paper demonstrates the applicability of the Quantum Walk-based Optimisation Algorithm(QWOA) to the Capacitated Vehicle Routing Problem (CVRP). Efficient algorithms are developedfor the indexing and unindexing of the solution space and for implementing the required alternatingphase-walk unitaries, which are the core components of QWOA. Results of numerical simulationdemonstrate that the QWOA is capable of producing convergence to near-optimal solutions for arandomly generated 8 location CVRP. Preparation of the amplified quantum state in this exampleproblem is demonstrated to produce high-quality solutions, which are more optimal than expectedfrom classical random sampling of equivalent computational effort.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2021 reference point for readers tracking recent quantum research.
  • This paper demonstrates the applicability of the Quantum Walk-based Optimisation Algorithm(QWOA) to the Capacitated Vehicle Routing Problem (CVRP).

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2109.14907 [2] arXiv https://arxiv.org/abs/2109.14907 [3] Publisher https://arxiv.org/abs/2109.14907

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