Eurasian container intermodal transportation network: a robust optimization with uncertainty and carbon emission constraints

Qi Xu^1*Xinying Huang¹Wei (Vera) Zhang²Hongzhuan Zhao¹Haiping Zhang³Zhihong Jin⁴

• ¹Guilin University of Electronic Technology, Guilin, China
• ²Australian Maritime College, University of Tasmania, Launceston, Australia, Launceston, Australia
• ³Haier Digital Technology (Qingdao) Co., Ltd, Qingdao, China
• ⁴Dalian Maritime University, Dalian, Liaoning Province, China

With the promotion of the “Belt and Road”, the container multimodal transportation between China and Europe has faced unprecedented development opportunities. In view of the increasing concern about carbon emissions and uncertainty during transportation, this paper constructs a robust optimization model with carbon emission constraints, and aims at minimizing both the operation cost and operation time. A Nondominated Sorting Genetic Algorithm-II (NSGA-II) is devised to tackle the proposed model. After that, the paper exemplifies with the container multimodal transportation from Nanjing, China to Berlin, Germany, conducting an empirical study on optimizing the Eurasian container multimodal transportation plan. A small-scale case compares the results from CPLEX and NSGA-II, validating the effectiveness of the proposed model and algorithm. Then, a comparison is made between the single-objective and multi-objective results. It is demonstrated that multi-objective optimization can resolve conflicts among sub-objectives and derive a compromise solution for multiple objectives. Subsequently, results under different fluctuation scenarios show that the robust model is applicable to all situations. Finally, a sensitivity analysis of the robust model is carried out, considering varying carbon emission limits, operating time windows, and regret values. The proposed model and algorithm can serve as a reliable decision reference for multimodal operators, remaining useful during unexpected incidents.