The application of formal optimization in identifying optimal combinations of a set of policy instruments has been demonstrated through the case studies that were present in this chapter. In doing so, the development of an objective function, and the ways in which financial constraints can be imposed, have also been illustrated in the chapter. The chapter has shown how policy instruments can be defined as continuous variables, within acceptable ranges, and allowed to vary by time of day or over time. The application has been illustrated with one transport model and one optimization routine, but two other routines that can be applied have also been described. While most of the results presented come directly from the optimization process, it also shows how sensitivity tests can be used to provide a richer understanding of the contribution of different instruments. The chapter has demonstrated that the use of response surfaces as a way of enhancing that understanding in different areas.
Abstract