Engineering system problems consist of multi-objective optimisation and the performance analysis is generally time consuming. To optimise the system concerning its performance, many researchers perform the optimisation using an approximation model. The Response Surface Method (RSM) is usually used to predict the system performance in many research fields, but it shows prediction errors for highly nonlinear problems. To create an appropriate metamodel for marine systems, Lee (2015) compares the prediction accuracy of the approximation model, and multi-objective optimal design framework is proposed based on a confirmed approximation model. The proposed framework is composed of three parts: definition of geometry, generation of approximation model, and optimisation.The major objective of this paper is to confirm the applicability/usability of the proposed optimal design framework and evaluate the prediction accuracy based on sensitivity analysis. We have evaluated the proposed framework applicability in derrick structure optimisation considering its structural performance. Keywords: Multi-objective optimal design framework, Sensitivity analysis, Back-Propagation Neural Network (BPNN), Neuro-Response Surface Method (NRSM), Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Derrick structure
A study on multi-objective optimal design of derrick structure: Case study
2018
Article (Journal)
Electronic Resource
Unknown
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