摘要
对于约束非线性规划问题,传统的方法:可行方向法、惩罚函数法计算烦琐且精度不高.用新兴的遗传算法来解决约束非线性规划,核心是惩罚函数的构造.以前的惩罚函数遗传算法有的精度较低,有的过于复杂.本文在两个定义的基础上构造了新的惩罚函数,并在新的惩罚函数的基础上,提出了一种解决约束非线性最优化问题的方法.通过两个例子应用Matlab说明了这个算法的可行性.
To optimization with nonlinear constraints programming, traditional method, such as feasible direction, penalty function, is complicated and imprecise. Solving optimization with nonlinear constraints programming by genetic algorithm, penalty function is core. The former genetic algorithm with penalty function is not perfect, imprecise and complicated. Based on two definition, the new penalty function is found. Throught new penalty function, the article develops the new method of solution of optimization with nonliear constraints programming. Two examples show that the improved method is effective.
出处
《大学数学》
北大核心
2005年第1期91-95,共5页
College Mathematics
基金
安徽省重点教学研究项目(2001011)
关键词
遗传算法
约束非线性规划
惩罚函数
交叉
变异
genetic algorithm
optimization with nonliear constraints programming
penalty function
mutation
crossover
