  This paper establishes the iteration-complexity of a Jacobi-type
non-Euclidean proximal alternating direction method of multipliers (ADMM) for
solving multi-block linearly constrained nonconvex programs. The subproblems of
this ADMM variant can be solved in parallel and hence the method has great
potential to solve large scale multi-block linearly constrained nonconvex
programs. Moreover, our analysis allows the Lagrange multiplier to be updated
with a relaxation parameter in the interval (0, 2).

Optimization and Control