In our previous work (Tian et al. Ind. Eng. Chem. Res. 2016, 55(21), 6161-6174), a plantwide scheduling model was presented, which was difficult to solve for industrial scale instances in acceptable time. Because the vinyl chloride monomer (VCM) buffer links the continuous process with the batch process, the whole scheduling problem can be decomposed into the upstream VCM production processes and the downstream polymerization processes. Thus, a decomposition algorithm is presented in this paper to accelerate the computation progress. Using the decomposition algorithm, the polymerization scheduling optimization problem is first conducted and thus the detailed VCM demand schedule is obtained. Then, with an off-line model formulated in advance, the operating states (i.e., start/stop operations) of arc furnaces are optimized in the second step, which would be the hard-to-solve binary variables in the plantwide scheduling model. In the off-line work, the furnaces operating range (i.e., the production rate) is discretized into multiple operational levels and the corresponding optimal furnaces selection scheme is then obtained based on the energy consumption model of the arc furnaces. Finally, the determined binary variables are embedded into the plantwide scheduling model and thus a reduced scale scheduling optimization is executed. Computational results show that the proposed algorithm can accelerate the computation greatly and the scheduling results are close to or even better than those given in our previous work.