摘要
设计了一种求非线性整数规划全局最小解的算法.首先,利用改进的遗传算法快速找到初始的离散局部极小解;其次,把该离散局部极小解作为初始点,用所设计的局部搜索算法极小化填充函数去寻找一个更好的局部极小解,并且通过有限次迭代,最后得到全局最小解.数值实验表明该算法是有效的.
This paper presents an algorithm to solve nonlinear integer programming problems. After trading out a discrete local minimal solution by using a genetic algorithm as a initial point, the algorithm tries to improve a discrete local minimal solution by minimizing a filled function. Finally, a global solution will be found after finite iterations. Numerical experiments show that this algorithm is efficient.
出处
《石家庄学院学报》
2006年第6期49-53,共5页
Journal of Shijiazhuang University
关键词
非线性整数规划
离散局部极小
填充函数
遗传算法
nonlinear integer programming
discrete local minimal solution
filled function method
genetic algorithm
