Abstract The research objective is to develop models and algorithms to provide quality solutions for large-scale service design problems. Service design problems arising at railroads, airlines, trucking firms, intermodal partnerships, etc. require the determination of the cost minimizing or profit maximizing set of services and their schedules, given limited resources and service requirements. The model is applied to a large express shipment transportation problem involving over 1.3 billion decision variables and 200,000 constraints. We develop a new model and solution approach — branch-and-price-and-cut. Computational results show that near optimal solution is achieved within a reasonable run time using novel problem reduction methods involving node consolidation, link consolidation, derived schedules and a branch-and-price-and-cut solution procedure.
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