The design of ship is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional design process of ship only involves independent design optimization within each discipline. With such an approach, there is no guarantee to achieve the optimum design. And at the same time improving the efficiency of ship optimization is also crucial for modem ship design. In this paper, an introduction of both the traditional ship design process and the fundamentals of Multidisciplinary Design Optimization (MDO) theory are presented and a comparison between the two methods is carried out. As one of the most frequently applied MDO methods, Collaborative Optimization (CO) promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, Design Of Experiment (DOE) and a new support vector regression algorithm are applied to CO to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method. Then this new Collaborative Optimization (CO) method using approximate technology is discussed in detail and applied in ship design which considers hydrostatic, propulsion, weight and volume, performance and cost. It indicates that CO method combined with approximate technology can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.
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ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering
July 1–6, 2012
Rio de Janeiro, Brazil
Conference Sponsors:
- Ocean, Offshore and Arctic Engineering Division
ISBN:
978-0-7918-4488-5
PROCEEDINGS PAPER
Support Vector Regression-Based Multidisciplinary Design Optimization for Ship Design Available to Purchase
Dongqin Li,
Dongqin Li
Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
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Yifeng Guan,
Yifeng Guan
Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
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Qingfeng Wang,
Qingfeng Wang
Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
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Zhitong Chen
Zhitong Chen
Jiangsu Modern Shipbuilding Technology, Ltd., Zhenjiang, Jiangsu, China
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Dongqin Li
Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
Yifeng Guan
Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
Qingfeng Wang
Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
Zhitong Chen
Jiangsu Modern Shipbuilding Technology, Ltd., Zhenjiang, Jiangsu, China
Paper No:
OMAE2012-83086, pp. 77-84; 8 pages
Published Online:
August 23, 2013
Citation
Li, D, Guan, Y, Wang, Q, & Chen, Z. "Support Vector Regression-Based Multidisciplinary Design Optimization for Ship Design." Proceedings of the ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering. Volume 1: Offshore Technology. Rio de Janeiro, Brazil. July 1–6, 2012. pp. 77-84. ASME. https://doi.org/10.1115/OMAE2012-83086
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