An advanced intermodal service network model for a practical transition to synchromodal transport in the US Freight System: A case study

Nasibeh Zanjirani Farahani, James Noble, Ronald Mcgarvey (mcgarveyr@missouri.edu) and Moein Enayati
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Nasibeh Zanjirani Farahani: Mayo Clinic [Rochester]
Ronald Mcgarvey: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Moein Enayati: Mayo Clinic [Rochester]

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Abstract: Free mode choice, termed "synchromodality," is an extension of intermodal service network design and is still in the early stages of modeling development. European countries have already started moving toward realizing this innovative transportation system. However, advancement in global transport with longer distances is rare and needs more infrastructural preparation and studies to clarify the steps for such a transition. In this paper, an advanced intermodal service network model (AI-SNM) is proposed to support the development of synchromodal transportation systems. This mixed-integer programming (MIP) model finds the optimal path between O/D pairs while considering horizontal integration of variant transport modes in a supply chain network along with resource constraints and time windows. It minimizes the total transportation cost, transshipment cost, and tardiness with a penalty for delays at intermodal terminals and overdue costs at the destination that accounts for the opening and closing times of the terminals. In order to solve the model for large problem instances, an efficient multiobjective genetic algorithm using a novel coding approach is developed. The algorithm is tested on two US-based case studies, showing the capability of the model to provide cost- and time-saving advantages in long-haul freight. The results of this study can be applied to long-distance global transportation with similar geography and scale.

Date: 2023-03
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Citations: View citations in EconPapers (2)

Published in Multimodal transportation, 2023, 2 (1), pp.100051. ⟨10.1016/j.multra.2022.100051⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04134439

DOI: 10.1016/j.multra.2022.100051

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