  In this paper, we propose an inertial accelerated primal-dual method for the
linear equality constrained convex optimization problem. When the objective
function has a ``nonsmooth + smooth'' composite structure, we further propose
an inexact inertial primal-dual method by linearizing the smooth individual
function and solving the subproblem inexactly. Assuming merely convexity, we
prove that the proposed methods enjoy $\mathcal{O}(1/k^2)$ convergence rate on
the objective residual and the feasibility violation in the primal model.
Numerical results are reported to demonstrate the validity of the proposed
methods.
