Frequently, urban transportation infrastructure and services are operated in a suboptimal manner with respect to key policy objectives such as enhancing mobility, avoiding severe congestion, improving public transit ridership, reducing fuel consumption, and emissions. To overcome this problem, a hybrid simulation-optimization methodology was developed for identification of values of demand management variables that result in the most favorable travel conditions in a multimodal corridor regarding a policy objective. This methodology was applied to a bus rapid transit based major travel corridor in Ottawa, Canada. The travel simulation part of the model is implemented within the EMME/2 modeling framework, supported by a transitway simulation technique. The optimization part of the methodology is based on direct search method that identifies the optimal values of key demand management variables for policy responsiveness. Optimization results are presentede for bus modal split, in-vehicle travel time, fuel consumption, and greenhouse gas emission.
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