Handling multiple objectives in optimization of externalities as objectives for dynamic traffic management


  • Luc Wismans University of Twente and DAT Mobility
  • Eric van Berkum University of Twente
  • Michiel Bliemer University of Sydney Business School




Dynamic traffic management (DTM) is acknowledged in various policy documents as an important instrument to improve network performance. This network performance is not only a matter of accessibility, since the externalities of traffic are becoming more and more important objectives as well. Optimization of network performance using DTM measures is a specific example of a network design problem (NDP) and incorporation of externality objectives results in a multi objective network design problem (MO NDP)). Solving this problem resorts in a Pareto optimal set of solutions. A framework is presented with the non-dominated sorting algorithm (NSGAII), the Streamline dynamic traffic assignment model and several externality models, that is used to solve this MO NDP. With a numerical experiment it is shown that the Pareto optimal set provides important information for the decision making process, which would not have been available if the optimization problem was simplified by incorporation of a compensation principle in advance. However, in the end a solution has to be chosen as the best compromise. Since the Pareto optimal set can be difficult to comprehend, ranking it may be necessary to assist the decision makers. Cost benefit analysis which uses the economic compensation principle is a method that is often used for ranking the alternatives. This research shows, that travel time costs are by far the most dominant objective. Therefore other ranking methods should be considered. Differences between these methods are explained and it is illustrated that the outcomes and therefore the eventual decisions taken can be different.


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How to Cite

Wismans, L., Berkum, E. van, & Bliemer, M. (2014). Handling multiple objectives in optimization of externalities as objectives for dynamic traffic management. European Journal of Transport and Infrastructure Research, 14(2). https://doi.org/10.18757/ejtir.2014.14.2.3023