Integrated land use and transport modelling has attracted the attention of researchers since 1960. Over the years, a large number of models have come into existence. It is well known that integration of land use and transport models creates a complex nonlinear system, which evolves in different scales. Analysing these complex systems is typically a hard problem, especially in the presence of uncertainty, whose effects may be difficult to assess. In such cases, calibration plays a central role, as it helps us determine optimal parameters. Calibrating this type of models is a process that requires many steps. At first, the data needed is not always readily available, but even if so, finding the set of parameters that replicates better the data is not simple. We propose an optimisation framework for the calibration of Tranus, particularly for obtaining a good estimation of the shadow-price variables.