半无限极大极小离散化问题的一个非单调SQCQP算法  

A Non-monotonic SQCQP Algorithm for Semi-infinite Minimax Discretization Problems

作　　者：杨永亮 王福胜[1] 甄娜 YANG Yongliang;WANG Fusheng;ZHEN Na(Department of Mathematics,Taiyuan Normal University,Jinzhong 030619,Shanxi Province,China)

机构地区：[1]太原师范学院数学系,山西晋中030619

出　　处：《吉林大学学报（理学版）》2020年第5期1107-1112,共6页Journal of Jilin University:Science Edition

基　　金：山西省回国留学人员科研项目(批准号:2017-104)。

摘　　要：针对序列二次规划(SQP)算法在处理结构复杂、非线性程度较大的半无限极大极小离散化问题时计算效率较低的不足,提出一种非单调序列二次约束二次规划(SQCQP)算法,并在适当的条件下证明算法的收敛性.数值实验结果表明,在离散水平为100的情形下,非单调类SQCQP算法在减少迭代次数和计算时间等方面均优于SQP算法.Aiming at the problem of low computational efficiency of sequential quadratic programming(SQP)algorithms when dealing with semi-infinite minimax discretization problems with complex structures and large nonlinearities,we proposed a non-monotonic sequential quadratic constrained quadratic programming(SQCQP)algorithm,and proved the converg ence of the algorithm under appropiate conditions.The results of numerical experiments show that the non-monotonic SQCQP algorithm is better than the SQP algorithm in reducing the number of iterations and calculation time when the discrete level is 100.

关 键 词：极大极小问题 模松弛 强次可行 SQCQP算法 非单调技术 

分 类 号：O224[理学—运筹学与控制论]