EURO 2025 Leeds
Abstract Submission

1774. Multi-objective cross-docking optimization under uncertainty in Physical Internet hubs

Invited abstract in session MC-17: Cross dock door platforms design, assigment and scheduling, stream Combinatorial Optimization.

Monday, 12:30-14:00
Room: Esther Simpson 2.08

Authors (first author is the speaker)

1. Fatma Essghaier
University of Artois
2. Tarik Chargui
LAMIH UMR CNRS 8201, Université Polytechnique Hauts-de-France
3. Hamid Allaoui
University of Artois

Abstract

The Physical Internet (PI) is an emerging paradigm designed to enhance the efficiency and interoperability of supply chains through open, hyper-connected networks. A key component of this system, cross-docking, enables the direct transfer of goods between inbound and outbound transport modes, reducing storage requirements and improving operational flow. However, managing such operations is inherently complex due to uncertainties, such as truck arrival times, capacity constraints, and real-time disruptions. These factors may cause inefficiencies and increase operational costs. Beyond these logistical challenges, supply chain sustainability and environmental concerns have become critical. To address these pressing issues, we propose an innovative truck scheduling approach for rail-road Physical Internet hubs. Our methodology employs Fuzzy Chance-Constrained Programming to effectively manage uncertainties in truck arrival times, while the ε-constraint method is used for multi-objective decision-making to minimize truck delays and reduce the cumulative energy consumption of PI-containers within the PI-conveying area. Preliminary analysis confirms the efficiency and robustness of our model. It shows that the integration of uncertainty management with multi-objective optimization significantly enhances operational efficiency and sustainability, promoting more resilient and environmentally conscious supply chains.

Keywords

Status: accepted

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