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Authors: Ahmed Azab 1 ; Ahmed Karam 2 and Amr Eltawil 1

Affiliations: 1 Egypt-Japan University of Science and Technology, Egypt ; 2 Faculty of Engineering at Shoubra and Benha University, Egypt

ISBN: 978-989-758-218-9

Keyword(s): Container Terminal, Integrated Simulation Optimization, Dynamic Model, Collaboration, Truck Appointment System.

Related Ontology Subjects/Areas/Topics: Agents ; Applications ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Information Systems Analysis and Specification ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Methodologies and Technologies ; Operational Research ; Optimization ; OR in Transportation ; Pattern Recognition ; Scheduling ; Simulation ; Software Engineering ; Symbolic Systems

Abstract: Given the rising growth in containerized trade, Container Terminals (CTs) are facing truck congestion at the gate and yard. Truck congestion problems not only result in long queues of trucks at the terminal gates and yards but also leads to long turn times of trucks and environmentally harmful emissions. As a result, many terminals are seeking to set strategies and develop new approaches to reduce the congestions in various terminal areas. In this paper, we tackle the truck congestion problem with a new dynamic and collaborative truck appointment system. The collaboration provides shared decision making among the trucking companies and the CT management, while the dynamic features of the proposed system enable both stakeholders to cope with the dynamic nature of the truck scheduling problem. The new Dynamic Collaboration Truck Appointment System (DCTAS) is developed using an integrated simulation-optimization approach. The proposed approach integrates an MIP model with a discrete even t simulation model. Results show that the proposed DCTAS could reduce the terminal congestions and flatten the workload peaks in the terminal. (More)

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Paper citation in several formats:
Azab A., Karam A. and Eltawil A. (2017). A Dynamic and Collaborative Truck Appointment Management System in Container Terminals.In Proceedings of the 6th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-218-9, pages 85-95. DOI: 10.5220/0006188100850095

@conference{icores17,
author={Ahmed Azab and Ahmed Karam and Amr Eltawil},
title={A Dynamic and Collaborative Truck Appointment Management System in Container Terminals},
booktitle={Proceedings of the 6th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2017},
pages={85-95},
doi={10.5220/0006188100850095},
isbn={978-989-758-218-9},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - A Dynamic and Collaborative Truck Appointment Management System in Container Terminals
SN - 978-989-758-218-9
AU - Azab A.
AU - Karam A.
AU - Eltawil A.
PY - 2017
SP - 85
EP - 95
DO - 10.5220/0006188100850095

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