MATEC Web of Conferences
Volume 52, 20162016 International Conference on Design Engineering and Science (ICDES 2016)
|Number of page(s)||10|
|Section||Chapter 2: Design Optimization|
|Published online||11 April 2016|
A Study on a Multi-Objective Optimization Method Based on Neuro-Response Surface Method (NRSM)
Department of Naval Architecture and Ocean Engineering, Pusan National University, Jangjeon 2-dong, Geumjeong-gu, Busan, South Korea, 609-717
a Corresponding author: email@example.com
The geometry of systems including the marine engineering problems needs to be optimized in the initial design stage. However, the performance analysis using commercial code is generally time-consuming. To solve this problem, many engineers perform the optimization process using the response surface method (RSM) to predict the system performance, but RSM presents some prediction errors for nonlinear systems. The major objective of this research is to establish an optimal design framework. The framework is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the response surface is generated using the artificial neural network (ANN) which is considered as NRSM. The optimization process is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case study of a derrick structure, we have confirmed the proposed framework applicability. In the future, we will try to apply the constructed framework to multi-objective optimization problems.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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