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Abstract An efficient global-local hybrid optimization method is developed combining a genetic algorithm as a global optimizer and a method of feasible direction as a local optimizer. During the global iteration using GA, the design senstivity information with respect to design variables is used to perform a what if study for efficient crossover. After the final global iteration, a local optimization can be followed to further improve the solution obtained from GA. The developed global local hybrid optimization method is applied to simple mathematical problems to compare the efficiency and accuracy of the proposed method with that of the conventional genetic algorithm. The application fo the developed method is alos extended to the practical engineering problems, whcih shows very good an efficient results.
Publication Date 2002-07-01
Role Coauthor
Category SCIE

Kyu-Yeul Lee, Seonho Cho, Myung-Il Roh, "An Efficient Global-Local Hybrid Optimization Method Using Design Sensitivity Analysis", International Journal of Vehicle Design, Vol. 28, No. 4, pp. 300-317, 2002.07.01


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