A Novel Truck Appointment System for Container Terminals

Fatima Bouyahia (), Sara Belaqziz, Youssef Meliani, Saâd Lissane Elhaq and Jaouad Boukachour
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Fatima Bouyahia: Laboratory of System Engineering & Applications, ENSA, Cadi Ayyad University, Marrakesh 40000, Morocco
Sara Belaqziz: Laboratory of System Engineering & Applications, ENSA, Cadi Ayyad University, Marrakesh 40000, Morocco
Youssef Meliani: Laboratory System and Materials for Mechatronics, Savoie Mont Blanc University, 73000 Chambéry, France
Saâd Lissane Elhaq: Engineering Research Laboratory ENSEM, Hassan II University of Casablanca, Casablanca 20676, Morocco
Jaouad Boukachour: IUT, Le Havre Normandy University, 76610 Le Havre, France

Sustainability, 2025, vol. 17, issue 13, 1-31

Abstract: Due to increased container traffic, the problems of congestion at terminal gates generate serious air pollution and decrease terminal efficiency. To address this issue, many terminals are implementing a truck appointment system (TAS) based on several concepts. Our work addresses gate congestion at a container terminal. A conceptual model was developed to identify system components and interactions, analyzing container flow from both static and dynamic perspectives. A truck appointment system (TAS) was modeled to optimize waiting times using a non-stationary approach. Compared to existing methods, our TAS introduces a more adaptive scheduling mechanism that dynamically adjusts to fluctuating truck arrivals, reducing peak congestion and improving resource utilization. Unlike traditional static appointment systems, our approach helps reduce truckers’ dissatisfaction caused by the deviation between the preferred time and the assigned one, leading to smoother operations. Various genetic algorithms were tested, with a hybrid genetic–tabu search approach yielding better results by improving solution stability and reducing computational time. The model was applied and adapted to the Port of Casablanca using real-world data. The results clearly highlight a significant potential to enhance sustainability, with an annual reduction of 785 tons of CO 2 emissions from a total of 1281 tons. Regarding trucker dissatisfaction, measured by the percentage of trucks rescheduled from their preferred times, only 7.8% of arrivals were affected. This improvement, coupled with a 62% decrease in the maximum queue length, further promotes efficient and sustainable operations.

Keywords: air pollution; truck appointment system; container terminal; metaheuristics; non-stationary queuing approach; Port of Casablanca (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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