摘要
In this paper, a new evolutionary strategy is proposed for minimizing uni- modal functions. Main characteristic of the strategy is that the classical mutation operator-Gaussian distribution is substituted by an uniform distribution. Theoretical analysis and numerical experiments indicate that convergence rate of the new strategy is superior to the classical one in most cases. Criteria of adoption of parent population and verification of step-length are also studied, and computa- tional efficiency of evolutionary strategies, in which crossover operator is employed or unemployed, is compared.
In this paper, a new evolutionary strategy is proposed for minimizing uni- modal functions. Main characteristic of the strategy is that the classical mutation operator-Gaussian distribution is substituted by an uniform distribution. Theoretical analysis and numerical experiments indicate that convergence rate of the new strategy is superior to the classical one in most cases. Criteria of adoption of parent population and verification of step-length are also studied, and computa- tional efficiency of evolutionary strategies, in which crossover operator is employed or unemployed, is compared.
出处
《计算数学》
CSCD
北大核心
2000年第4期465-472,共8页
Mathematica Numerica Sinica
