Abstract
The mixed-integer linear programming (MILP) model is introduced in this article for the formulation of the bi-objective problem of minimizing total delivery time and greenhouse gas (GHG) emissions in multimodal and intermodal freight transportation for the delivery of a full container unit from Ningbo, China to Kasur, Pakistan. In this study, a multiobjective genetic algorithm is used to address the optimization problem (MOGA). The Pareto optimum solution from MOGA helps decision-makers to make the best trade-off between environmentally friendly and time-saving modes of transportation. We chose the clothing industry for real-world data collecting using EXW incoterms and conditions from one of Pakistan’s leading logistics service providers. According to our research, direct shipping delivery from the Ningbo seaport to the Karachi seaport minimizes delivery time by 11% when compared to intermodal freight distribution. Furthermore, when moving a single container from China to Pakistan, our research on GHG emissions shows that multimodal freight transportation is 19% more environmentally friendly than intermodal freight transit. Second, we looked at how each mode of transportation affected overall emissions in multimodal and intermodal freight transportation.
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Shoukat, R., Xiaoqiang, Z. Is multimodal transportation greener and faster than intermodal in full container load? A case from Pakistan–China. Energy Syst (2023). https://doi.org/10.1007/s12667-023-00596-x
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DOI: https://doi.org/10.1007/s12667-023-00596-x