摘要
基于惩罚函数的思想，提出了沿权重梯度方向变异的遗传算法（ＧＡ）求解非线性规划问题．该方法既避免了惩罚函数法在计算上的困难，也无需传统遗传算法所要求的复杂的编码和译码过程．给出了收敛性分析．一些实例的仿真结果表明算法的有效性．
Based on the method of penalty function,an improved Genetic Algorithm with mutation along the weighted gradient direction for nonlinear programming problems is proposed in this paper. It will avoid the computer difficulty existing in the penalty function method,but also it does not need the complex coding and decoding process necessary for traditional genetic algorithm. Simulation of some examples shows that this method is effective.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
1997年第5期490-493,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金
关键词
非线性规划
遗传算法
权重梯度方向
收敛性
nonlinear programming,penalty function,convergency,genetic algorithm,weighted gradient direction.
