Robustness evaluation of a physical internet-based intermodal logistic network

The Physical Internet (PI) paradigm, which has gained attention in research and academia in recent years, leverages advanced logistics and interconnected networks to revolutionise the way goods are transported and delivered, thereby enhancing efficiency, reducing costs and delays, and minimising env...

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Main Authors: Federico Gallo, Alireza Shahedi, Angela Di Febbraro, Mahnam Saeednia, Nicola Sacco
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Transportation Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666691X25000338
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author Federico Gallo
Alireza Shahedi
Angela Di Febbraro
Mahnam Saeednia
Nicola Sacco
author_facet Federico Gallo
Alireza Shahedi
Angela Di Febbraro
Mahnam Saeednia
Nicola Sacco
author_sort Federico Gallo
collection DOAJ
description The Physical Internet (PI) paradigm, which has gained attention in research and academia in recent years, leverages advanced logistics and interconnected networks to revolutionise the way goods are transported and delivered, thereby enhancing efficiency, reducing costs and delays, and minimising environmental impact. Within this system, PI-hubs function similarly to cross-docks, enabling the splitting of PI-containers into smaller modules for delivery through a network of interconnected hubs. This allows dynamic routing optimisation and efficient consolidation of PI-containers. However, the impact of system parameters and relevant uncertainties on the performance of this innovative logistics framework is still unclear. For this reason, this work proposes a robustness analysis to understand how the PI logistics framework is affected by the handling, consolidation, and processing of PI-containers at PI-hubs. To this end, the considered PI logistics system is represented via a mathematical programming model that determines the best allocation of PI-containers in an intermodal setting with different transportation modes. In doing so, four Key Performance Indicators (KPIs) are separately considered to investigate different aspects of the PI system’s performance, and the relevant robustness is assessed with respect to the PI-hub processing times and the number of modules per PI-container. In particular, a Global Sensitivity Analysis (GSA) is performed to evaluate, through a case study, the individual relevance of each input parameter on the resulting performance.
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spelling doaj-art-fa0c1332ed764f6c808cdf0c581f20fd2025-08-20T03:53:12ZengElsevierTransportation Engineering2666-691X2025-06-012010033310.1016/j.treng.2025.100333Robustness evaluation of a physical internet-based intermodal logistic networkFederico Gallo0Alireza Shahedi1Angela Di Febbraro2Mahnam Saeednia3Nicola Sacco4Dept. of Mechanical, Energy, Management, and Transport Engineering, University of Genoa, Via Montallegro 1, Genoa, 16145, ItalyDept. of Mechanical, Energy, Management, and Transport Engineering, University of Genoa, Via Montallegro 1, Genoa, 16145, ItalyDept. of Mechanical, Energy, Management, and Transport Engineering, University of Genoa, Via Montallegro 1, Genoa, 16145, ItalyDept. of Transport and Planning, Delft University of Technology, Postbus 5, Delft, 2600 AA, The NetherlandsDept. of Mechanical, Energy, Management, and Transport Engineering, University of Genoa, Via Montallegro 1, Genoa, 16145, Italy; Corresponding author.The Physical Internet (PI) paradigm, which has gained attention in research and academia in recent years, leverages advanced logistics and interconnected networks to revolutionise the way goods are transported and delivered, thereby enhancing efficiency, reducing costs and delays, and minimising environmental impact. Within this system, PI-hubs function similarly to cross-docks, enabling the splitting of PI-containers into smaller modules for delivery through a network of interconnected hubs. This allows dynamic routing optimisation and efficient consolidation of PI-containers. However, the impact of system parameters and relevant uncertainties on the performance of this innovative logistics framework is still unclear. For this reason, this work proposes a robustness analysis to understand how the PI logistics framework is affected by the handling, consolidation, and processing of PI-containers at PI-hubs. To this end, the considered PI logistics system is represented via a mathematical programming model that determines the best allocation of PI-containers in an intermodal setting with different transportation modes. In doing so, four Key Performance Indicators (KPIs) are separately considered to investigate different aspects of the PI system’s performance, and the relevant robustness is assessed with respect to the PI-hub processing times and the number of modules per PI-container. In particular, a Global Sensitivity Analysis (GSA) is performed to evaluate, through a case study, the individual relevance of each input parameter on the resulting performance.http://www.sciencedirect.com/science/article/pii/S2666691X25000338Physical internetFreight transportationLogisticsRobustness analysisGlobal sensitivity analysis (GSA)
spellingShingle Federico Gallo
Alireza Shahedi
Angela Di Febbraro
Mahnam Saeednia
Nicola Sacco
Robustness evaluation of a physical internet-based intermodal logistic network
Transportation Engineering
Physical internet
Freight transportation
Logistics
Robustness analysis
Global sensitivity analysis (GSA)
title Robustness evaluation of a physical internet-based intermodal logistic network
title_full Robustness evaluation of a physical internet-based intermodal logistic network
title_fullStr Robustness evaluation of a physical internet-based intermodal logistic network
title_full_unstemmed Robustness evaluation of a physical internet-based intermodal logistic network
title_short Robustness evaluation of a physical internet-based intermodal logistic network
title_sort robustness evaluation of a physical internet based intermodal logistic network
topic Physical internet
Freight transportation
Logistics
Robustness analysis
Global sensitivity analysis (GSA)
url http://www.sciencedirect.com/science/article/pii/S2666691X25000338
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