Improving the computational eciency for optimization of oshore wind turbine jacket substructure by Hybrid Algorithms
Journal
Journal of Marine Science and Engineering
Journal Volume
8
Journal Issue
8
Start Page
548
Date Issued
2020-08
Author(s)
Abstract
When solving real-world problems with complex simulations, utilizing stochastic algorithms integrated with a simulation model appears inefficient. In this study, we compare several hybrid algorithms for optimizing an offshore jacket substructure (JSS). Moreover, we propose a novel hybrid algorithm called the divisional model genetic algorithm (DMGA) to improve efficiency. By adding different methods, namely particle swarm optimization (PSO), pattern search (PS) and targeted mutation (TM) in three subpopulations to become “divisions,” each division has unique functionalities. With the collaboration of these three divisions, this method is considerably more efficient in solving multiple benchmark problems compared with other hybrid algorithms. These results reveal the superiority of DMGA in solving structural optimization problems.
Publisher
MDPI AG
Type
journal article