摘要
提出一个求解非线性互补问题的混合遗传算法,即首先将非线性互补问题转化为等价的最优化问题,然后利用浮点遗传算法全局群体搜索能力及起始搜索速度快的特点,快速得到接近精确解的近似解。之后将其作为牛顿法或拟牛顿法的初始值,利用其局部寻优能力非常强的特点,快速迭代至满足精度要求的数值解。该混合遗传算法充分利用了浮点遗传算法和(拟)牛顿法的各自优点。数值结果表明该方法是有效的。
In this paper, we propose a hybrid genetic algorithm for solving nonlinear complemen-tarity problems （denoted by NCP）. First, we transform NCP into the equivalent optimization problems. Then we use the floating genetic algorithms to gain the superior results which is close to precise solutions. These results are then taken as the initial values of Newton or quasi-Newton iterations, which have strong ability in locally converging to precise solution. We obtain satisfactory approximation solutions. the floating genetic algorithm and Newton-typemethods. the given problem. The hybrid genetic algorithm absorbs fully the merits of Numerical results show that this method is effective for the given problem.
出处
《桂林电子科技大学学报》
2008年第2期108-110,共3页
Journal of Guilin University of Electronic Technology
基金
国家自然科学基金(10661005)
广西自然科学基金(桂科自0640165)
关键词
非线性互补问题
混合遗传算法
牛顿法
拟牛顿法
nonlinear complementarity problem
hybrid genetic algorithm
Newton method
quasi-Newton method
