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http://dx.doi.org/10.3795/KSME-A.2003.27.11.1809

Global Optimization Using Differential Evolution Algorithm  

Jung, Jae-Joon (한양대학교 대학원 기계설계학과)
Lee, Tae-Hee (한양대학교 기계공학부)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.27, no.11, 2003 , pp. 1809-1814 More about this Journal
Abstract
Differential evolution (DE) algorithm is presented and applied to global optimization in this research. DE suggested initially fur the solution to Chebychev polynomial fitting problem is similar to genetic algorithm(GA) including crossover, mutation and selection process. However, differential evolution algorithm is simpler than GA because it uses a vector concept in populating process. And DE turns out to be converged faster than CA, since it employs the difference information as pseudo-sensitivity In this paper, a trial vector and its control parameters of DE are examined and unconstrained optimization problems of highly nonlinear multimodal functions are demonstrated. To illustrate the efficiency of DE, convergence rates and robustness of global optimization algorithms are compared with those of simple GA.
Keywords
Differential Evolution Algorithm; Global Optimization; Genetic Algorithm; Crossover Process; Mutation process;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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