Abstract
A great number of functional evaluations may be required until reaching the convergence in the process of optimization. Although the approximation models constructed by the response surface methodology are usually used to get the optimal designs, it is thought that the design accuracy is dependent on the type of activate functions and the design region of interest. In this paper, techniques to search all the local optimal designs within the feasible design region, and techniques for finding more accurate approximation using Holographic Neural Network (HNN) are investigated. Furthermore, the proposed method is applied to the problems frequently encountered in design of automobiles such as increasing of energy dissipation in crashworthiness and reducing of interior noise to illustrate the effectiveness of the proposed method.
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