Based on the flexibility of multi energy technology, integrated energy network can provide services for regional and higher level energy systems. Due to the nonlinear factors and the complexity of modeling, the operational uncertainty is often ignored in optimal control modeling. Therefore, this paper proposes an integrated energy network optimization control framework including multi energy controllable devices. The improved mixed integer linear programming (MILP) and the linear approximation of nonlinear network equations are applied to the two-stage iterative modeling of the framework. In the MILP optimization stage, based on the power balance equivalent model of electricity, heat and natural gas, and introducing the uncertain probability factor, the uncertain operation is set constrained, and the optimization objective function of cost minimization is established. In the second iteration stage, the nonlinear synthesis network model is used, and the random probability factor set of differential parameters is introduced. In order to improve the efficiency and feasibility of iterative approximation calculation, the dynamic correction strategy of linear constraint independent parameters is introduced into the iteration process. Finally, the proposed optimization control model is applied to an industrial park, and the experimental results show that the optimization model calculation method can maximize the energy consumption cost, ensure the calculation efficiency and adapt to the uncertainty of the integrated energy network.