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Implementation and acceleration of optimal control for systems biology
Optimal control theory provides insight into complex resource allocation decisions. The forward–backward sweep method (FBSM) is an iterative technique commonly implemented to solve two-point boundary value problems arising from the application of Pontryagin’s maximum principle (PMP) in optimal contr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8385371/ https://www.ncbi.nlm.nih.gov/pubmed/34428951 http://dx.doi.org/10.1098/rsif.2021.0241 |
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author | Sharp, Jesse A. Burrage, Kevin Simpson, Matthew J. |
author_facet | Sharp, Jesse A. Burrage, Kevin Simpson, Matthew J. |
author_sort | Sharp, Jesse A. |
collection | PubMed |
description | Optimal control theory provides insight into complex resource allocation decisions. The forward–backward sweep method (FBSM) is an iterative technique commonly implemented to solve two-point boundary value problems arising from the application of Pontryagin’s maximum principle (PMP) in optimal control. The FBSM is popular in systems biology as it scales well with system size and is straightforward to implement. In this review, we discuss the PMP approach to optimal control and the implementation of the FBSM. By conceptualizing the FBSM as a fixed point iteration process, we leverage and adapt existing acceleration techniques to improve its rate of convergence. We show that convergence improvement is attainable without prohibitively costly tuning of the acceleration techniques. Furthermore, we demonstrate that these methods can induce convergence where the underlying FBSM fails to converge. All code used in this work to implement the FBSM and acceleration techniques is available on GitHub at https://github.com/Jesse-Sharp/Sharp2021. |
format | Online Article Text |
id | pubmed-8385371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-83853712021-08-26 Implementation and acceleration of optimal control for systems biology Sharp, Jesse A. Burrage, Kevin Simpson, Matthew J. J R Soc Interface Review Articles Optimal control theory provides insight into complex resource allocation decisions. The forward–backward sweep method (FBSM) is an iterative technique commonly implemented to solve two-point boundary value problems arising from the application of Pontryagin’s maximum principle (PMP) in optimal control. The FBSM is popular in systems biology as it scales well with system size and is straightforward to implement. In this review, we discuss the PMP approach to optimal control and the implementation of the FBSM. By conceptualizing the FBSM as a fixed point iteration process, we leverage and adapt existing acceleration techniques to improve its rate of convergence. We show that convergence improvement is attainable without prohibitively costly tuning of the acceleration techniques. Furthermore, we demonstrate that these methods can induce convergence where the underlying FBSM fails to converge. All code used in this work to implement the FBSM and acceleration techniques is available on GitHub at https://github.com/Jesse-Sharp/Sharp2021. The Royal Society 2021-08-25 /pmc/articles/PMC8385371/ /pubmed/34428951 http://dx.doi.org/10.1098/rsif.2021.0241 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Review Articles Sharp, Jesse A. Burrage, Kevin Simpson, Matthew J. Implementation and acceleration of optimal control for systems biology |
title | Implementation and acceleration of optimal control for systems biology |
title_full | Implementation and acceleration of optimal control for systems biology |
title_fullStr | Implementation and acceleration of optimal control for systems biology |
title_full_unstemmed | Implementation and acceleration of optimal control for systems biology |
title_short | Implementation and acceleration of optimal control for systems biology |
title_sort | implementation and acceleration of optimal control for systems biology |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8385371/ https://www.ncbi.nlm.nih.gov/pubmed/34428951 http://dx.doi.org/10.1098/rsif.2021.0241 |
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