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http://dx.doi.org/10.3795/KSME-A.2014.38.5.535

Robust Optimization Using Supremum of the Objective Function for Nonlinear Programming Problems  

Lee, Se Jung (Dept. of Mechanical Engineering, Hanyang Univ.)
Park, Gyung Jin (Dept. of Mechanical Engineering, Hanyang Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.38, no.5, 2014 , pp. 535-543 More about this Journal
Abstract
In the robust optimization field, the robustness of the objective function emphasizes an insensitive design. In general, the robustness of the objective function can be achieved by reducing the change of the objective function with respect to the variation of the design variables and parameters. However, in conventional methods, when an insensitive design is emphasized, the performance of the objective function can be deteriorated. Besides, if the numbers of the design variables are increased, the numerical cost is quite high in robust optimization for nonlinear programming problems. In this research, the robustness index for the objective function and a process of robust optimization are proposed. Moreover, a method using the supremum of linearized functions is also proposed to reduce the computational cost. Mathematical examples are solved for the verification of the proposed method and the results are compared with those from the conventional methods. The proposed approach improves the performance of the objective function and its efficiency.
Keywords
Robust Optimization; Robustness Index; Supremum function; Optimum Sensitivity;
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