Implementation and acceleration of optimal control for systems biology.

Autor:	Sharp JA; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.; ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Australia., Burrage K; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.; ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Australia.; Department of Computer Science, University of Oxford, Oxford OX2 6GG, UK., Simpson MJ; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.
Jazyk:	angličtina
Zdroj:	Journal of the Royal Society, Interface [J R Soc Interface] 2021 Aug; Vol. 18 (181), pp. 20210241. Date of Electronic Publication: 2021 Aug 25.
DOI:	10.1098/rsif.2021.0241
Abstrakt:	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.
Databáze:	MEDLINE
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