吉林大学学报(理学版) ›› 2020, Vol. 58 ›› Issue (5): 1107-1112.

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半无限极大极小离散化问题的一个非单调SQCQP算法

杨永亮, 王福胜, 甄娜   

  1. 太原师范学院 数学系, 山西 晋中 030619
  • 收稿日期:2019-12-05 出版日期:2020-09-26 发布日期:2020-11-18
  • 通讯作者: 王福胜 E-mail:fswang2005@163.com

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

YANG Yongliang, WANG Fusheng, ZHEN Na   

  1. Department of Mathematics, Taiyuan Normal University, Jinzhong 030619, Shanxi Province, China
  • Received:2019-12-05 Online:2020-09-26 Published:2020-11-18

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.

关键词: 极大极小问题, 模松弛, 强次可行, SQCQP算法, 非单调技术

Abstract: 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 convergence 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.

Key words: minimax problem, norm-relaxed, strongly sub-feasible,  , SQCQP algorithm, non-monotonic technique

中图分类号: 

  • O224