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Application of Quantum Annealing to Nurse Scheduling Problem

Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice. We investigate the empirical performance of quantum annealing to solve the...

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Autores principales: Ikeda, Kazuki, Nakamura, Yuma, Humble, Travis S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731278/
https://www.ncbi.nlm.nih.gov/pubmed/31492936
http://dx.doi.org/10.1038/s41598-019-49172-3
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author Ikeda, Kazuki
Nakamura, Yuma
Humble, Travis S.
author_facet Ikeda, Kazuki
Nakamura, Yuma
Humble, Travis S.
author_sort Ikeda, Kazuki
collection PubMed
description Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice. We investigate the empirical performance of quantum annealing to solve the Nurse Scheduling Problem (NSP) with hard constraints using the D-Wave 2000Q quantum annealing device. NSP seeks the optimal assignment for a set of nurses to shifts under an accompanying set of constraints on schedule and personnel. After reducing NSP to a novel Ising-type Hamiltonian, we evaluate the solution quality obtained from the D-Wave 2000Q against the constraint requirements as well as the diversity of solutions. For the test problems explored here, our results indicate that quantum annealing recovers satisfying solutions for NSP and suggests the heuristic method is potentially achievable for practical use. Moreover, we observe that solution quality can be greatly improved through the use of reverse annealing, in which it is possible to refine returned results by using the annealing process a second time. We compare the performance of NSP using both forward and reverse annealing methods and describe how this approach might be used in practice.
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spelling pubmed-67312782019-09-18 Application of Quantum Annealing to Nurse Scheduling Problem Ikeda, Kazuki Nakamura, Yuma Humble, Travis S. Sci Rep Article Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice. We investigate the empirical performance of quantum annealing to solve the Nurse Scheduling Problem (NSP) with hard constraints using the D-Wave 2000Q quantum annealing device. NSP seeks the optimal assignment for a set of nurses to shifts under an accompanying set of constraints on schedule and personnel. After reducing NSP to a novel Ising-type Hamiltonian, we evaluate the solution quality obtained from the D-Wave 2000Q against the constraint requirements as well as the diversity of solutions. For the test problems explored here, our results indicate that quantum annealing recovers satisfying solutions for NSP and suggests the heuristic method is potentially achievable for practical use. Moreover, we observe that solution quality can be greatly improved through the use of reverse annealing, in which it is possible to refine returned results by using the annealing process a second time. We compare the performance of NSP using both forward and reverse annealing methods and describe how this approach might be used in practice. Nature Publishing Group UK 2019-09-06 /pmc/articles/PMC6731278/ /pubmed/31492936 http://dx.doi.org/10.1038/s41598-019-49172-3 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ikeda, Kazuki
Nakamura, Yuma
Humble, Travis S.
Application of Quantum Annealing to Nurse Scheduling Problem
title Application of Quantum Annealing to Nurse Scheduling Problem
title_full Application of Quantum Annealing to Nurse Scheduling Problem
title_fullStr Application of Quantum Annealing to Nurse Scheduling Problem
title_full_unstemmed Application of Quantum Annealing to Nurse Scheduling Problem
title_short Application of Quantum Annealing to Nurse Scheduling Problem
title_sort application of quantum annealing to nurse scheduling problem
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731278/
https://www.ncbi.nlm.nih.gov/pubmed/31492936
http://dx.doi.org/10.1038/s41598-019-49172-3
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