Freight route planning in intermodal transportation network to deal with combinational disruptions

Abstract

In this study, we developed an intermodal transportation model that extends the VRP model and its recovery model. This study emphasizes re-identifying the best route, departure time, and the selection of the best ship with the right type of capacity booking that produces the lowest total cost after dealing with disruption. The re-routing process is shifted by transforming the disruption to a virtual node in order to define the added time and cost after a disruption occurred. The disruption types include link and customer disruptions. The numerical experiment uses the metaheuristics, namely, Genetic Algorithm and Simulated Annealing, because it is an np-hard problem. The results of the optimization process yielded the total cost increased when the average vehicle speed was enhanced. The starting service time provides cost savings through a reduction of penalties because the arrival is not within the time window that had been agreed upon. Besides, the type of capacity order, more specifically the type of direct purchase (on the spot), provides better costs when the level of disruption is heavy. In contrast, a lighter level of disruption can cause a minimal total cost for purchasing the up-front type of fee. However, the scenario of capacity cost shows that lower prices can make the direct purchasing type more profitable. On the other hand, increasing the price of renting a ship’s capacity makes the up-front type of fees more profitable.

Keywords

• customer disruptions
• link disruptions
• intermodal
• freight routing planning
• capacity booked
• time appointment
• genetic algorithm
• simulated annealing