A new variation of the user equilibrium discrete network design problem (UE-DNDP) is proposed for achieving Environmental Justice (EJ) or equity amongst population groups. This research is motivated by the federal requirement that transportation plans using federal money include an evaluation of EJ and that the planning agency mitigate, where feasible, any disproportionately disparate impacts to protected populations (i.e. minority and low-income groups). Nine potential objective functions focused on maximizing equity of congestion and travel time are developed and discussed as to their applicability for the upper level of this bilevel problem. Assuming knowledge of the origin-destination travel matrices by population group, numerical analysis is conducted to assess the performance of each proposed formulation. The lower level UE problem is solved using the Frank-Wolfe method, and due to the hard combinatorial nature of EJ-UE-DNDP, a selectorecombinative genetic algorithm is implemented to efficiently search the solution space for feasible network improvement strategies. The results of numerical analysis suggest that both pareto-optimal and utility-based approaches can be successfully applied, and that the most effective formulations minimize the difference between the change in congestion or travel time across population groups due to the selected improvement projects.
Abstract