A hybrid optimization approach for designing sustainable intermodal freight transport under mixed uncertainty

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8 Citations (Scopus)

Abstract

Intermodal freight transport stands out as an innovative logistics solution for combating climate change. However, the intricacies of planning resilient and sustainable intermodal freight transport systems necessitate further investigation. Addressing this critical research gap, this paper introduces a pioneering hybrid optimization framework tailored for designing a robust rail-road intermodal network that prioritizes sustainability while navigating disruptions and operational uncertainties. This framework adopts a multi-period approach to model intricate intermodal operations, including mode-switching activities. It strategically determines optimal locations for intermodal terminals and makes tactical decisions regarding inventory management and transport planning. The goal is to enhance the sustainability performance of intermodal terminals while simultaneously minimizing the overall total cost and carbon emissions of the network. The sustainability assessment of intermodal terminals employs a variant of network data envelopment analysis, considering a range of conflicting measures. Furthermore, the proposed optimization approach integrates P-robust and possibilistic chance-constraint programming to effectively mitigate disruption risks and operational uncertainties inherent in intermodal networks. To validate the efficacy of the proposed approach, two datasets are utilized, including a real-world case study of rail-road intermodal freight transport. The numerical findings showcase the significant benefits of this approach, demonstrating a remarkable 24 % reduction in maximum regret with a negligible 1.4 % increase in expected cost, highlighting its potential for sustainable and resilient intermodal freight transport systems. This research provides valuable insights for freight transport companies to enhance resilience against disruptions and manage operational uncertainties, while also contributing to societal goals of sustainable development through reduced environmental impacts.

Original languageEnglish
Article number102146
JournalSocio-Economic Planning Sciences
Volume98
DOIs
Publication statusPublished - Apr 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  4. SDG 13 - Climate Action
    SDG 13 Climate Action

!!!Keywords

  • Disruption
  • Intermodal freight transport
  • Network data envelopment analysis
  • Resilience
  • Sustainability
  • Uncertainty

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