Energy efficiency optimization and energy management can bring multiple economic benefits for the complicated petrochemical industries. However, the influence of the production scale and materials, and the uncertain data have a direct impact on the production prediction and energy efficiency optimization of ethylene production process, which is ignored by the conventional optimization strategies. To achieve energy management and reduce energy consumption considering the production technology, total energy, and material flows, a multiobjective energy efficiency optimization scheme for the ethylene production process with respect to material-product nexus is proposed. Specifically, a total-factor material-product nexus model of the ethylene production is established by a novel functional link prediction error method-integrated algorithm, providing system-level material equilibrium constraints for the energy efficiency optimization scheme. Then an optimization model with two mutually complementary energy efficiency indicators is established and implemented by the multiobjective particle swarm optimization integrating functional link prediction error method. The proposed energy efficiency optimization scheme is applied into a practical ethylene plant, and the optimization results demonstrate that energy efficiency of this plant is increased by 10.30%, synthetical energy consumption is decreased by 13.05%, and energy cost is decreased by 10.42%.