运筹学学报 >
2018 , Vol. 22 >Issue 2: 79 - 92
DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2018.02.007
线性约束两分块非凸优化的ADMM-SQP算法
收稿日期: 2017-11-08
网络出版日期: 2018-06-15
基金资助
国家自然科学基金 (Nos. 11771383, 11601095), 广西自然科学基金 (Nos. 2016GXNSFDA380019, 2016GXNSFBA380185)
ADMM-SQP algorithm for two blocks linear constrained nonconvex optimization
Received date: 2017-11-08
Online published: 2018-06-15
简金宝, 劳译娴, 晁绵涛, 马国栋 . 线性约束两分块非凸优化的ADMM-SQP算法[J]. 运筹学学报, 2018 , 22(2) : 79 -92 . DOI: 10.15960/j.cnki.issn.1007-6093.2018.02.007
Based on the alternating direction method of multipliers (ADMM) and the sequential quadratic programming (SQP) method, this paper proposes a new efficient algorithm for two blocks nonconvex optimization with linear constrained. Firstly, taking SQP thought as the main line, the quadratic programming (QP) is decomposed into two independent small scale QP according to ADMM idea. Secondly, the new iteration point of the prime variable is generated by Armijo line search for the augmented Lagrange function. Finally, the dual variables are updated by an explicit expression. Thus, a new ADMM-SQP algorithm is constructed. Under the weaker conditions, the global convergence of the algorithm is analyzed. Some preliminary numerical results are reported to support the efficiency of the new algorithm.
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