非线性约束优化一个强收敛的广义投影强次可行方向法  

A generalized projection of strongly sub-feasible direction method with strong convergence for nonlinear constrained optimization

作　　者：简金宝[1] 郭传好[1] 陈越华[2] 

机构地区：[1]广西大学数学与信息科学学院,广西南宁530004 [2]广西师范学院物理与电子信息科学系,广西南宁530001

出　　处：《高校应用数学学报（A辑）》2009年第2期194-200,共7页Applied Mathematics A Journal of Chinese Universities(Ser.A)

基　　金：国家自然科学基金(10771040);广西自然科学基金(0832052);广西教育厅科研项目(200807MS151)

摘　　要：讨论带非线性不等式和等式约束的最优化问题,借助强次可行方向法和半罚函数的思想,给出了问题的一个新的广义投影强次可行方向法.该算法的一个重要特性是有限次迭代后,迭代点落入半罚问题的可行域.在适当的条件下证明了算法的全局收敛性和强收敛性.数值实验表明算法是有效的.In this paper, the optimization problems with nonlinear inequality and equality constraints are discussed. With the help of strongly sub-feasible direction method and the idea of semipenalty function, a new generalized projection of strongly sub-feasible direction method for the discussed problems is proposed. An outstanding property of the proposed algorithm is that the iteration points can enter into the feasible region of the semi-penalty problem after a finite number of iterations. Under some suitable conditions, the globally and strongly convergent properties are obtained. The numerical experiments show that the proposed algorithm is promising.

关 键 词：非线性约束 广义投影 强次可行方向法 强收敛性 

分 类 号：O221.2[理学—运筹学与控制论]