Many steel products are produced in hot or cold rolling lines with multiple stands. The steel material becomes thinner after being rolled at each stand. Steady-state parameters for controlling the rolling line need to be set so as to satisfy the final product specifications and minimize the total energy consumption. This paper develops a generalized geometric programming model for this setting problem and proposes a global method for solving it. The

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Since how to quickly and accurately set the optimal process parameter of each mill in the cold rolling production process is an important base task for energy saving technology of cold rolling process now, this task designed a cold rolling process operation optimization simulation system based on Visual C++ and HMI software. Its design idea, system architecture and function were introduced. For the changes of model parameters and uncertain measurement data under different conditions for the cold rolling process, in order to enhance the reliability of system model, the optimization model and MPC control model of rolling force for cold rolling mill were built. Modified particle swarm optimization (PSO) intelligent algorithm is used to solve the proposed rolling force optimization model and MPC control model. The Visual C++ was used to implement optimization algorithms and system integration, establish the real-time cold rolling process simulation platform. Then HMI software was used to make the user interface of simulation platform. Finally, the feasibility and practical value of this simulation experimental platform were demonstrated by the cold rolling process optimization simulation system. The simulation results indicate that this system has its strongpoint that it can collect and dispose the data simply, quickly and timely, also this system is helpful in optimization and improvement real-time optimization model and control of rolling force in cold rolling process, and the method and simulation system have obviously optimization effect for various working conditions, and meet the requirements of actual production.