It is crucial to accurately predict and control the overall microstructure uniformity of large forgings to enhance their comprehensive mechanical properties. Common empirical models of dynamic recrystallization (DRX) do not consider the nucleation mechanisms and grain boundary migration driven by stored energy differences, thereby limiting their ability to predict and track nucleation events and microstructure morphology during the DRX process. To address this limitation, this study proposes an effective simulation approach for microstructure morphology evolution by integrating the level-set method with a dislocation model. The level set function, implemented on a fixed grid within the Eulerian framework, enables the numerical tracking of evolving curves or surfaces on Cartesian grids. Further, it also facilitates topological evolution handling, thereby eliminating the need for complex curve or surface parameterization. Parameters of the DRX model based on the level set method were determined using stress-strain experimental data of the GH4706 alloy within the temperature range of 950-1150 ^oC and strain rate range of 0.001-1 s^-1. Although certain model parameters were obtained through fitting, the two critical parameters of nucleation volume per unit time at the grain boundary surface and factor affecting grain boundary migration rate could not be determined in this way. These were instead identified using a Pareto multi-objective optimization method, which iteratively minimized the discrepancy between experimental data and simulated results through reverse analysis. The DRX fraction and the average grain size were selected as the optimization objectives. The average deviation percentages between the experimental data and simulated results of the two optimization objectives under varying strain conditions were used as evaluation functions. Through continuous multi-objective iterative optimization, an optimal parameter set was derived. Simulation results for the GH4706 alloy under different parameter combinations revealed a linear relationship between the DRX model parameters with the process variables. The DRX behavior of the GH4706 alloy under strains of 0.4-0.7 was simulated and experimentally validated. A comparison between the experimental data and simulation results showed that the average deviation of both the DRX grain volume fraction fraction and grain size was less than 10%. This confirmed the validity of the model and parameter identification approach. Thus, this study provides a robust theoretical framework for simulating the microstructure uniformity of GH4706 alloy during large forgings and offers valuable insights for predicting and regulating the microstructural uniformity.