Impact and relevance of transit disturbances on planning in intermodal container networks using disturbance cost analysis
In North-West Europe, the options for intermodal inland transportation of containers are increasing. Inland corridors become increasingly interconnected in hinterland networks. To minimise operating costs, new methods are required that allow integral network operations management. The network operations consist of allocating containers to available inland transportation services, that is, planning. For adequate planning it is important to adapt to occurring disturbances. In this article, a new mathematical model is proposed: the Linear Container Allocation model with Time-restrictions. This model is used for determining the influence of three main types of transit disturbances on network performance: early service departure, late service departure and cancellation of inland services. The influence of a disturbance is measured in two ways. The impact measures the additional cost incurred by an updated planning in case of a disturbance. The relevance measures the cost difference between a fully updated and a locally updated plan. With the results of the analysis, key service properties of disturbed services that result in a high impact or high relevance can be determined. Based on this, the network operator can select focus areas to prevent disturbances with high impact and to improve the planning updates in case of disturbances with high relevance. The proposed method is used in a case study to assess the impact and relevance of transit disturbances on inland services of the European Gateway Services network.
|Keywords||container transportation, disturbances, Intermodal, synchromodal planning|
|Persistent URL||dx.doi.org/10.1057/mel.2014.27, hdl.handle.net/1765/91464|
|Journal||Maritime Economics & Logistics|
van Riessen, B, Negenborn, R.R, Lodewijks, G, & Dekker, R. (2015). Impact and relevance of transit disturbances on planning in intermodal container networks using disturbance cost analysis. Maritime Economics & Logistics, 17(4), 440–463. doi:10.1057/mel.2014.27