摘要
针对基本混沌优化算法在求解三维以上的多维函数时不易求得全局最优解的局限性,通过引入解向量的优选,提出了一种改进的混沌优化算法,主要思路是通过多次可行解向量的混沌优选,将可行解定位到最优解的附近,再用二次载波进行搜索找出多维函数的全局最优解.仿真计算表明:该算法对三维以上函数可以显著提高搜索精度,收敛性能好,容易找到全局最优解.
Due to the difficulties of finding global optimization solutions to multi-dimensional functions using the chaos optimization algorithm, a modified chaos optimization algorithm is developed based on the optimization of solution vectors. With several iterations of optimization, the solution vectors approach the optimal solution, and the global optimal solutions to the multi-dimensional functions can be found by the carrier wave two times. Simulation results show that this method significantly improves the search accuracy and convergent behavior and is effective in finding global optimal solutions to multi-dimensional functions.
出处
《河海大学学报（自然科学版）》
CAS
CSCD
北大核心
2008年第3期423-426,共4页
Journal of Hohai University(Natural Sciences)
基金
河海大学常州校区创新基金(CC2007-004)
关键词
混沌
混沌优化算法
函数优化
解向量优选
chaos
the chaos optimization algorithm
function optimization
solution vector optimization
