Scenario-Scaping with Inverse Programming for Intermodal Transportation

We study an intermodal transportation problem over a long-term planning horizon where scenarios involving different equipment, location and network arcs are possible. We model the problem as a capacitated multi-commodity network flow problem and make use of inverse programming techniques to sketch the landscape of the uncertain scenario cost function to show when one scenario becomes preferable to another. We apply reduction, preprocessing and heuristic methods to solve some steps our procedure.