Differentiated road pricing schemes are defined by different design dimensions, such as a price level for each road section, for each time, and fordifferent road users. Different policy objectives lead to different optimal designs of schemes. The problem is to find the optimal price levels to meet the policy objectives, which are mathematically formulated in an objective function. The price levels can however not be varied freely, as public acceptance, user understanding of the system, etc. impose social constraints. In this study, different pattern search algorithms and different objective functions (policy objectives) are discussed. Furthermore, other methods like grid search and genetic algorithms are compared in a qualitative analysis. To test the optimisation approach a modelling framework is used that includes a departure time choice model to determine the effects of changes in dynamic travel costs and travel times. The effects of these changes on route choice and the resulting network flows are determined using a macroscopic dynamic traffic assignment model with multiple user classes.The level of demand may change using an elastic demand approach. The optimisation framework is tested on two real cases in the Netherlands: a roughnetwork of the town of Delft and a more detailed network of the city of The Hague and the two surrounding towns of Zoetermeer and Delft. These area's are all in the western part of the Netherlands and they include severalmajor motorways. For the Delft network a solution with 15% less congestion than a logical predefined toll setting has been found. With regard to the situation without road pricing the congestion has been reduced by 41%. Similar results are found for the larger and more detailed The Hague network, but need to be further researched. For the covering abstract see ITRD E145999
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