Objective function can be decomposed into n independent convex functions, and the constraint conditions for linear constraint can be divided into convex optimization problem. This paper presents a kind of promotion forecast correction multiplier method to solve separable convex optimization problem, this algorithm uses the second item in the iteration to replace the augmented Lagrangian function of the augmented items, and the proposed algorithm has both the characterization of neighboring multiplier method and parallel computation as well as can guarantee the global convergence under weak condition.