Agent-based modeling is a powerful tool that is widely used to model global financial systems. When the parameters of the model are appropriate, the price time series generated by the model exhibit marked similarities with actual financial time series and even reproduces some of their statistical characteristics.By using Kirman’s Ant model as a prototype, this report systematically explored Gilli and Winker’s parameter optimization method. In view of some limitations of this method, this report promoted some improvements, including a local-restart strategy to enhance the convergence ability of the original optimization method, as well as incorporate Simulated Annealing into the original method to help the algorithm escape from local optimums. Furthermore, since the parameter optimization of agent-based modeling tends to be very time-consuming, an acceleration method was also proposed to speed up this procedure. In the end, the presented methods have been validated with the EUR/USD exchange rate.