The exclusive and excessive use of long-distance road transportation is not suitable way to reduce the negative environmental impacts of logistics systems. Intermodal transport, combining road with other transport modes, has the potential to reduce both operating costs and carbon footprints. One of the reasons for the low share of intermodal transport is its requirement for the coordination of scheduled transport services that can result in reducing reliability in case of disruptions due to the arrival of new shipment orders, fluctuations in shipment quantities, delays, and service cancellations within the network. This calls for reliable and efficient algorithms to replan the shipments’ distribution. In this paper, the replanning problem is formulated as a path-based multi-commodity network flows. We provide two different network topologies, one of which is based on a time–space network, while the other embeds time aspect in a highly scalable alternative structure to large transportation networks. We propose a column generation method whose pricing sub-problems are presented as resource constrained shortest path problem solved via a tailored label-correcting algorithm. We look at the pros and cons of complete and partial replanning in case of disruption and provide managerial insights for intermodal networks. An extensive set of computational experiments is presented on realistic instances being generated with the consultation of our industrial partners for a logistic network including railways, waterways, and roads. The promising outcomes validate the efficiency of the proposed approach that can be easily adjusted to real-time intermodal logistic replanning.

The cargo fare class mix (CFCM) problem aims to find the optimal fare class mix for a given intermodal transportation network based on known client demands. It is based on a revenue management problem for aviation passengers, the fare class mix problem, but considering intermodal cargo transportation, two major differences apply. Firstly, the CFCM’s premise is that long-term commitments to customers must be provided, such that a customer has a guaranteed daily capacity. Secondly, cargo may be rescheduled or rerouted, as long as the customer’s delivery due date is met. Our goal is to balance revenue maximisation and capacity utilisation by optimally combining two delivery service levels. Therefore, the optimisation problem is to select fare class limits at a tactical level up to which transportation demand will be accepted on a daily basis at the operational level. Any accepted demand that does not fit on the available network capacity during operation, must be transported by truck at increased expenses for the network operator. In this paper, we propose a faster method than the previously proposed solution method for a single corridor network and we provide proofs for the optimality of the result. Using this, we extend the problem to an intermodal network of multiple corridors. We provide numerical results for different settings, in which we compare the baseline of individual corridor optimums with the result of using rerouting. Finally, we apply the methods in a case study for an intermodal transportation network in North-West Europe.

The intermodal hinterland transportation of maritime containers is under pressure from port authorities and shippers to achieve a more integrated, efficient network operation. Current optimisation methods in literature yield limited results in practice, though, as the transportation product structure limits the flexibility to optimise network logistics. Synchromodality aims to overcome this by a new product structure based on differentiation in price and lead time. Each product is considered as a fare class with a related service level, allowing to target different customer segments and to use revenue management for maximising revenue. However, higher priced fare classes come with tighter planning restrictions and must be carefully balanced with lower priced fare classes to match available capacity and optimise network utilisation. Based on the developments of intermodal networks in North West European, such as the network of European Gateway Services, the Cargo Fare Class Mix problem is proposed. Its purpose is to set limits for each fare class at a tactical level, such that the expected revenue is maximised, considering the available capacity at the operational level. Setting limits at the tactical level is important, as it reflects the necessity of long-term agreements between the transportation provider and its customers. A solution method for an intermodal corridor is proposed, considering a single intermodal connection towards a region with multiple destinations. The main purpose of the article is to show that using a limit on each fare class increases revenue and reliability, thereby outperforming existing fare class mix policies, such as Littlewood.

Hinterland networks for container transportation require planning methods in order to increase efficiency and reliability of the inland road, rail and waterway connections. In this paper we aim to derive real-time decision rules for suitable allocations of containers to inland services by analysing the solution structure of a centralised optimisation method used offline on historic data. The decision tree can be used in a decision support system (DSS) for instantaneously allocating incoming orders to suitable services, without the need for continuous planning updates. Such a DSS is beneficial, as it is easy to implement in the current practice of container transportation. Earlier proposed centralised methods can find the optimal solution for the intermodal inland transportation problem in retrospect, but are not suitable when information becomes gradually available. The main contributions are threefold: firstly, a structured method for creating decision trees from optimal solutions is proposed. Secondly, an innovative method is used for obtaining multiple equivalent optimal solutions to prevent overfitting of the decision tree. And finally, a structured analysis of three error types is presented for assessing the quality of an obtained tree. A case study illustrates the method's purpose by comparing the quality of the resulting plan with alternative methods.