Efficient Parallel Solution of Large-Scale Nonlinear Dynamic Optimization Problems
(2014) In Computational Optimization and Applications 59(3). p.667-688- Abstract
- This paper presents a decomposition strategy applicable to DAE constrained optimization problems. A common solution method for such problems is to apply a direct transcription method and solve the re- sulting nonlinear program using an interior-point algorithm. For this approach, the time to solve the linearized KKT system at each iteration typically dominates the total solution time. In our proposed method, we exploit the structure of the KKT system resulting from a direct collocation scheme for ap- proximating the DAE constraints in order to compute the necessary linear algebra operations on multiple processors. This approach is applied to find the optimal control profile of a combined cycle power plant with promising results on both... (More)
- This paper presents a decomposition strategy applicable to DAE constrained optimization problems. A common solution method for such problems is to apply a direct transcription method and solve the re- sulting nonlinear program using an interior-point algorithm. For this approach, the time to solve the linearized KKT system at each iteration typically dominates the total solution time. In our proposed method, we exploit the structure of the KKT system resulting from a direct collocation scheme for ap- proximating the DAE constraints in order to compute the necessary linear algebra operations on multiple processors. This approach is applied to find the optimal control profile of a combined cycle power plant with promising results on both distributed memory and shared memory computing architectures with speedups of over 50 times possible. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3972728
- author
- Word, Daniel ; Kang, Jia ; Laird, Carl and Åkesson, Johan LU
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Computational Optimization and Applications
- volume
- 59
- issue
- 3
- pages
- 667 - 688
- publisher
- Springer
- external identifiers
-
- wos:000344803000011
- scopus:84927123259
- ISSN
- 0926-6003
- DOI
- 10.1007/s10589-014-9651-2
- language
- English
- LU publication?
- yes
- id
- 09519dfc-cec6-400b-bb05-c344e170ebe2 (old id 3972728)
- date added to LUP
- 2016-04-01 14:05:44
- date last changed
- 2024-05-08 19:21:16
@article{09519dfc-cec6-400b-bb05-c344e170ebe2,
abstract = {{This paper presents a decomposition strategy applicable to DAE constrained optimization problems. A common solution method for such problems is to apply a direct transcription method and solve the re- sulting nonlinear program using an interior-point algorithm. For this approach, the time to solve the linearized KKT system at each iteration typically dominates the total solution time. In our proposed method, we exploit the structure of the KKT system resulting from a direct collocation scheme for ap- proximating the DAE constraints in order to compute the necessary linear algebra operations on multiple processors. This approach is applied to find the optimal control profile of a combined cycle power plant with promising results on both distributed memory and shared memory computing architectures with speedups of over 50 times possible.}},
author = {{Word, Daniel and Kang, Jia and Laird, Carl and Åkesson, Johan}},
issn = {{0926-6003}},
language = {{eng}},
number = {{3}},
pages = {{667--688}},
publisher = {{Springer}},
series = {{Computational Optimization and Applications}},
title = {{Efficient Parallel Solution of Large-Scale Nonlinear Dynamic Optimization Problems}},
url = {{http://dx.doi.org/10.1007/s10589-014-9651-2}},
doi = {{10.1007/s10589-014-9651-2}},
volume = {{59}},
year = {{2014}},
}