Operations Research Transactions >
2023 , Vol. 27 >Issue 3: 37 - 52
DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2023.03.003
A class of inertial symmetric regularization alternating direction method of multipliers for nonconvex two-block optimization
Received date: 2021-04-21
Online published: 2023-09-14
The alternating direction method of multipliers(ADMM) is an valid method for solving separable convex optimization problems, nevertheless, when the objective function has a nonconvex function, ADMM may not converge. This paper proposes an inertial symmetric regularization alternating direction method of multipliers for nonconvex two-block optimization problem with linear equality constraints. Under the appropriate hypothesis conditions, the global convergence of the algorithm is established. Secondly, When the benefit function satisfies the Kurdyka-Łojasiewicz(KL) property, the strong convergence of the algorithm is established. Finally, numerical experiments are performed on the algorithm, and the results show that the algorithm is an effective method.
Jianwen PENG, Hongwang LEI . A class of inertial symmetric regularization alternating direction method of multipliers for nonconvex two-block optimization[J]. Operations Research Transactions, 2023 , 27(3) : 37 -52 . DOI: 10.15960/j.cnki.issn.1007-6093.2023.03.003
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