The Pareto set as decision support information in multimodal passenger transportation network design

Given a range of traffic related sustainability problems, policy makers need to know which measures should be taken to reach their objectives as much as possible. Multi-objective optimisation is useful to support these decisions, because it results in an overview of possibly optimal solutions. This Pareto set can be very large, especially if more than two (mainly opposed) objectives are involved. This is also the case when optimising infrastructure planning in a multimodal passenger transportation network, with accessibility, use of urban space by parking, operating deficit and climate impact as objectives. Methods are presented to derive problem knowledge from the Pareto set. This includes the best values per objective, average trade-off values between pairs of objectives and identification of the min-max solution. These methods make the Pareto set more useful as decision support information: they demonstrate the next step in multi-objective option prioritisation. An insight provided for a case study in the Amsterdam Metropolitan Area in The Netherlands is that it is possible to improve all aspects of sustainability simultaneously in comparison to the current transportation network: the current design is not part of the Pareto set. Next, improving travel time further can be done cost-efficiently, but reducing CO2 emissions is expensive when using measures related to multimodal trip making. Finally, increasing frequencies appears to be more effective to improve sustainability than introducing P&R facilities and train stations.