Optimization techniques are commonly used for parameter estimation in a wide variety of applications. The application described here is a laser flash thermal diffusivity experiment on a layered sample where the thermal properties properties of some of the layers are unknown. The aim is to estimate the unknown properties by minimising, in a least squares sense, the difference between model predictions and measured data. Two optimization techniques have been applied to the problem. Results suggest that the classical nonlinear least-square optimizer is more efficient than PSO for this type of problem. Results have also highlighted the importance of defining a suitable objective function and choosing appropriate parameters.