Time-window based Truck Appointment System with Adaptive Slot management and Real-Time Truck Information

A case study for the loading operations in a Chemical Plant

Master thesis (2024)

Authors

V. Skoulas Civil Engineering & Geosciences

Contributors

Lorant Tavasszy (graduation committee member)
Ron van Duin Transport and Logistics - TPM (mentor)
M.B. Duinkerken Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (mentor)
R. Vanga Transport and Logistics - TPM (mentor)
Faculty
Civil Engineering & Geosciences, Civil Engineering & Geosciences
Copyright: © 2024 Vasileios Skoulas
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Published Date

19-01-2024

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

Long truck queues and congestion around terminals is a common sight, however they come with many negative externalities for all the stakeholders involved. Truck Appointment System (TAS) is the most commonly used system to face these problems, but it still has some drawbacks and limitations. Consequently, in this research an extension of the typical TAS is proposed in order to improve its performance. The main components of this system are the use of truck dependent time-windows, the utilization of real-time information and the adaptive trucks rescheduling model. The duration of the arrival time-windows is longer than the actual service times, allowing overlap between time-windows. Thus, the actual service sequence might be different from the reserved one. To determine the actual loading sequence an Optimization model is developed, which is run periodically while utilizing real-time truck information. A chemical plant is used as a case study in this research. The performance of the proposed TAS is assessed with the use of a Simulation model. The outcomes of this research suggest that the a less strict TAS can significantly improve the system’s performance, especially trucks’ waiting times. Also, the system’s resilience against disruptions and the plant’s environmental footprint are improved, while queues are reduced.