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http://dx.doi.org/10.3795/KSME-A.2014.38.5.489

Development of Optimization Algorithm Using Sequential Design of Experiments and Micro-Genetic Algorithm  

Lee, Jung Hwan (Dept. of Automotive Engineering, Osan Univ.)
Suh, Myung Won (School of Mechanical Engineering, Sungkyunkwan Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.38, no.5, 2014 , pp. 489-495 More about this Journal
Abstract
A micro-genetic algorithm (MGA) is one of the improved forms of a genetic algorithm. It is used to reduce the number of iterations and the computing resources required by using small populations. The efficiency of MGAs has been proved through many problems, especially problems with 3-5 design variables. This study proposes an optimization algorithm based on the sequential design of experiments (SDOE) and an MGA. In a previous study, the authors used the SDOE technique to reduce trial-and-error in the conventional approximate optimization method by using the statistical design of experiments (DOE) and response surface method (RSM) systematically. The proposed algorithm has been applied to various mathematical examples and a structural problem.
Keywords
Sequential Design of Experiments(SDOE); Micro-Genetic Algorithm; Response Surface Method; Artificial Neural Network(ANN);
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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