Abstract
Compared with traditional freight transportation, intermodal freight transportation is more competitive which can combine the advantages of different transportation modes. As a consequence, operational research on intermodal freight transportation has received more attention and developed rapidly, but it is still a young research field. In this paper, a stochastic intermodal service network design problem is introduced in a sea-rail transportation system, which considers stochastic travel time, stochastic transfer time, and stochastic container demand. Given candidate train and ship services, we develop a two-stage chance constrained programming model for this problem with the objective of minimising the expected total cost. The first stage allows for the selection of operated services, while the second stage focuses on the determination of intermodal container routes where capacity and on-time delivery chance constraints are presented. A hybrid heuristic algorithm, incorporating sample average approximation and ant colony optimisation, is employed to solve this model. The proposed model is applied to a realistic intermodal sea-rail network, which demonstrates the performance of the model and algorithm as well as the influence of stochasticity on transportation plans. Hence, the proposed methodology can improve effectively the performance of intermodal service network design scheme under stochastic conditions and provide managerial insights for decision-makers.
Highlights
As a vital component of logistics and economy, intermodal freight transportation (IFT) facilitates international trade among most countries in the world
The stochastic intermodal service network design (SISND) problem with stochastic travel time, transfer time, and container demand is formulated as a two-stage chance constrained programming model to minimise total cost in an intermodal sea-rail network
A hybrid heuristic algorithm incorporating Sample average approximation (SAA) method and ant colony optimisation (ACO) algorithm is proposed to solve the SISND problem under capacity and on-time delivery chance constraints with predetermined confidence levels
Summary
As a vital component of logistics and economy, intermodal freight transportation (IFT) facilitates international trade among most countries in the world. Meng et al [23] presented a linear programming model to formulate the intermodal liner shipping SND in an inland and maritime network. Meng et al [26] reviewed the research on containership routing and scheduling problems and indicated that there are too many uncertainties in containerised maritime transportation, such as container demand [27], port time [28], and travel time [29]. In the maritime system, stochasticity at sea and port poses a big challenge for liner shipping companies because of unexpected weather and variable operation efficiency Modelling these components by their expected values cannot capture the characteristics of real-life problems. Demir et al [35] developed a stochastic intermodal mixed integer programming model for the green intermodal SND with uncertain travel time and uncertain demand.
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