WANG Xin, GUO Ke. Convergence of the Generalized Alternating Direction Method of Multipliers for a Class of Nonconvex Optimization Problems[J]. Applied Mathematics and Mechanics, 2018, 39(12): 1410-1425. doi: 10.21656/1000-0887.380334
Citation: WANG Xin, GUO Ke. Convergence of the Generalized Alternating Direction Method of Multipliers for a Class of Nonconvex Optimization Problems[J]. Applied Mathematics and Mechanics, 2018, 39(12): 1410-1425. doi: 10.21656/1000-0887.380334

Convergence of the Generalized Alternating Direction Method of Multipliers for a Class of Nonconvex Optimization Problems

doi: 10.21656/1000-0887.380334
Funds:  The National Natural Science Foundation of China(11571178; 11801455)
  • Received Date: 2017-12-27
  • Rev Recd Date: 2018-10-18
  • Publish Date: 2018-12-01
  • The generalized alternating direction method of multipliers (GADMM) for the minimization problems of the sum of 2 functions with linear constraints was considered, where one function was convex and the other can be expressed as the difference of 2 convex functions. For each subproblem in the GADMM, the linearization technique in the convex function difference algorithm was employed. Under the assumptions that the associated functions satisfy the Kurdyka-ojasiewicz inequality, the sequence generated with the GADMM converges to a critical point of the augmented Lagrangian function, while the penalty parameter in the augmented Lagrangian function is sufficiently large. At last, the convergence rate of the algorithm was established.
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