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What is Robustness of Objective and Constraint Functions

Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications
The robustness of objective function makes the objective function insensitive to the variations due to noises. On the contrary, the robustness of constraint function is defined by the feasibility condition satisfying design requirements.
Published in Chapter:
Metamodel-Based Optimum Design Examples of Structures
Kwon-Hee Lee (Dong-A University, Republic of Korea) and Ji-In Heo (Dong-A University, Republic of Korea)
DOI: 10.4018/978-1-4666-4450-2.ch022
Abstract
In order to achieve greater fuel efficiency and energy conservation, the reduction of weight and enhancement of the performance of structures has been sought. In general, there are two approaches to reducing structural weight. One of which is to use materials that are lighter than steel and the other is to redesign the structure. However, conventional structural optimization methods using gradient-based algorithm directly have difficulties in defining complex shape design variables and preventing mesh distortions. To overcome these difficulties a metamodel-based optimization method is introduced in order to replace the true response by an approximate one. This research presents four case studies of structural design using a metamodel-based approximation model for weight reduction or performance enhancement.
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