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Quantum Optimization Quantum Machine Learning Quantum Simulation

Quantum Walk-Based Vehicle Routing Optimisation

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Authors: T. Bennett, E. Matwiejew, S. Marsh, J. B. Wang

Year

2021

Paper ID

13651

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

96

Citations

16

Abstract

This paper demonstrates the applicability of the Quantum Walk-based Optimisation Algorithm (QWOA) to the Capacitated Vehicle Routing Problem (CVRP). Efficient algorithms are developed for the indexing and unindexing of the solution space and for implementing the required alternating phase-walk unitaries, which are the core components of QWOA. Results of numerical simulation demonstrate that the QWOA is capable of producing convergence to near-optimal solutions for a randomly generated eight location CVRP. Preparation of the amplified quantum state in this example problem is demonstrated to produce higher-quality solutions than expected from classical random sampling of equivalent computational effort.

Why This Paper Matters

  • 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/10.3389/fphy.2021.730856 [2] Publisher https://doi.org/10.3389/fphy.2021.730856

Local Citation Graph (Related-Paper Links)

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External citation index: OpenAlex citation signal • updated 2026-10-22 12:28:06

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