Abstract
As one of main challenge for carriers, empty container repositioning is subject to various uncertain factors in practice, which causes more operation costs. At the same time, the movements of empty containers can result in air pollution because of the CO2 emission, which has a negative impact on sustainable development. To incorporate environmental and stochastic characteristics of container shipping, in this paper, an empty container repositioning problem, taking into account CO2 emission, stochastic demand, and supply, is introduced in a sea–rail intermodal transportation system. This problem is formulated as a chance-constrained nonlinear integer programming model minimising the expected value of total weighted cost. A sample average approximation method is applied to convert this model into its deterministic equivalents, which is then solved by the proposed two-phase tabu search algorithm. A numerical example is studied to conclude that the stochastic demand and supply lead to more repositioning and CO2 emission-related cost. Total cost, inventory cost, and leasing cost increase with the variabilities of uncertain parameters. We also found that the total cost and other component costs are strongly dependent on the weights of repositioning cost and CO2 emission-related cost. Additionally, the sensitivity analysis is conducted on unit leasing cost.
Highlights
Due to the overwhelming growth of international trade in recent years, international freight transportation develops rapidly
This paper focuses on the empty container repositioning problem (ECRP), with the consideration of leasing decisions and CO2 emissions in an intermodal sea–rail network
Lee et al [32] focused on the joint container fleet sizing problem, and ECRP with the consideration of stochastic demand based on the feedback mechanism of inventory information, while Dong et al [33] compared the results of different empty container repositioning policies under uncertain demand
Summary
Due to the overwhelming growth of international trade in recent years, international freight transportation develops rapidly. Crainic et al [23] focused on the ECRP that involved stochastic demand and supply modelled as random variables in the context of the land transportation of international maritime shipping. Lee et al [32] focused on the joint container fleet sizing problem, and ECRP with the consideration of stochastic demand based on the feedback mechanism of inventory information, while Dong et al [33] compared the results of different empty container repositioning policies under uncertain demand. To incorporate environmental and stochastic characteristics of container shipping, this paper proposes a chance-constrained programming model for ECRP in an intermodal transportation system, which allows for, explicitly, CO2 emissions and uncertainty simultaneously.
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