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1 이대우, "유전 이론을 이용한 위성 임무 스케줄링 알고리즘의 제어상수에 따른 적합도 변화 연구" 제어·로봇·시스템학회 16 (16): 572-578, 2010
2 G. Rudolph, "Self adaptive mutations lead to premature convergence" 5 (5): 410-414, 2001
3 M. Affenzeller, "SASEGASA: An evolutionary algorithm for retarding premature convergence by self-adaptive selection pressure steering, Computational Methods in Neural Modelling" Springer 2686 : 438-445, 2003
4 문병로, "Raising Mutation Rate in the Context of Hybrid Genetic Algorithms" ACM 157-158, 2011
5 P. N. Suganthan, "Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization" Natural Computing Laboratory, Department of Computer Science, National Chiao Tung University 2005
6 M. Rocha, "Preventing premature convergence to local optima in genetic algorithms via random offspring generation" 127-136, 1999
7 H. Wang, "Opposition-based particle swarm algorithm with cauchy mutation" 4750-4756, 2007
8 B. Chakraborty, "On the use of genetic algorithm with elitism in robust and nonparametric multivariate analysis" 32 (32): 13-27, 2003
9 H.-K. Lee, "On parameter selection for reducing premature convergence of genetic algorithms" 214-219, 2010
10 S.-H. Bae, "Mutation rates in the context of hybrid genetic algorithms" 381-382, 2004
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