摘要
提出一种基于实数编码的变容差遗传算法,该算法是将自适应遗传算法的随机性与可变容差算法的确定性相结合,利用可变容差算法的准行域搜索准则,对具有非线性、多峰、多约束的问题寻优.运用该混合算法对有边界限制的6个峰值、4个性能约束的复杂函数最大值多次寻优,并与罚函数处理约束条件后的结果相比较,表明该算法依据容差准则具有较高的可靠性,尤其对于隐性约束,在一定精度范围内能够提高收敛精度,减少计算量,提高优化效率.
A hybrid method combining a genetic proposed for global optimization problems with algorithm with a flexible tolerance algorithm is multiple nonlinear constraints and peaks. The adaptive genetic algorithm is used to localize the ＂best＂ areas, while the flexible tolerance algorithm exploits this area by search mechanism for quasi-feasible point. To evaluate the efficiency of this method, a complex function with six peaks and four constraints is implemented and compared with the results supplied by sequential uniconstrained minimization technique（SUMT）, which indicates that the hybrid method is able to improve convergence and reduce computing task greatly.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2007年第11期1267-1270,共4页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(50575175)
关键词
自适应遗传算法
可变容差算法
约束
寻优
adaptive genetic algorithm
flexible tolerance algorithm
muhiconstraint
optimization
