Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm
This paper presents a method of multiobjective optimization based on approximation model for dynamic umbilical installation. The optimization aims to find out the most cost effective size, quantity and location of buoyancy modules for umbilical installation. Due to the highly geometrically nonlinear...
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ftuglasgow:oai:eprints.gla.ac.uk:158171 2023-05-15T14:26:08+02:00 Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm Wang, Aijun Yang, Hezhen Li, Huajun 2011-06 http://eprints.gla.ac.uk/158171/ unknown Wang, A., Yang, H. <http://eprints.gla.ac.uk/view/author/44914.html> and Li, H. (2011) Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm. In: 30th International Conference on Ocean, Offshore and Arctic Engineering, Rotterdam, The Netherlands, 19–24 June 2011, ISBN 9780791844366 (doi:10.1115/OMAE2011-49148 <http://dx.doi.org/10.1115/OMAE2011-49148>) Conference Proceedings PeerReviewed 2011 ftuglasgow https://doi.org/10.1115/OMAE2011-49148 2020-01-10T01:36:42Z This paper presents a method of multiobjective optimization based on approximation model for dynamic umbilical installation. The optimization aims to find out the most cost effective size, quantity and location of buoyancy modules for umbilical installation. Due to the highly geometrically nonlinearity and highly responsive dynamic nature in deepwater, dynamic umbilical analysis is very complex and time-consuming. Approximation Model constructed by design of experiment (DOE) sampling is utilized to solve this problem. Non-linear dynamic analyses considering environmental loadings are executed on these sample points from DOE. Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed to obtain the Pareto solution set through an evolutionary optimization process. The optimization results indicate this optimization strategy with approximation model is valid, and provide the optimal deployment way of buoyancy modules. Conference Object Arctic University of Glasgow: Enlighten - Publications Volume 4: Pipeline and Riser Technology 121 129 |
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University of Glasgow: Enlighten - Publications |
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ftuglasgow |
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description |
This paper presents a method of multiobjective optimization based on approximation model for dynamic umbilical installation. The optimization aims to find out the most cost effective size, quantity and location of buoyancy modules for umbilical installation. Due to the highly geometrically nonlinearity and highly responsive dynamic nature in deepwater, dynamic umbilical analysis is very complex and time-consuming. Approximation Model constructed by design of experiment (DOE) sampling is utilized to solve this problem. Non-linear dynamic analyses considering environmental loadings are executed on these sample points from DOE. Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed to obtain the Pareto solution set through an evolutionary optimization process. The optimization results indicate this optimization strategy with approximation model is valid, and provide the optimal deployment way of buoyancy modules. |
format |
Conference Object |
author |
Wang, Aijun Yang, Hezhen Li, Huajun |
spellingShingle |
Wang, Aijun Yang, Hezhen Li, Huajun Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm |
author_facet |
Wang, Aijun Yang, Hezhen Li, Huajun |
author_sort |
Wang, Aijun |
title |
Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm |
title_short |
Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm |
title_full |
Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm |
title_fullStr |
Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm |
title_full_unstemmed |
Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm |
title_sort |
multiobjective optimization for dynamic umbilical installation using non-dominated sorting genetic algorithm |
publishDate |
2011 |
url |
http://eprints.gla.ac.uk/158171/ |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
Wang, A., Yang, H. <http://eprints.gla.ac.uk/view/author/44914.html> and Li, H. (2011) Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm. In: 30th International Conference on Ocean, Offshore and Arctic Engineering, Rotterdam, The Netherlands, 19–24 June 2011, ISBN 9780791844366 (doi:10.1115/OMAE2011-49148 <http://dx.doi.org/10.1115/OMAE2011-49148>) |
op_doi |
https://doi.org/10.1115/OMAE2011-49148 |
container_title |
Volume 4: Pipeline and Riser Technology |
container_start_page |
121 |
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129 |
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1766298610903810048 |