Alagesan, Vignesh (2017) Investigating congestion mitigation scenarios to reduce truck turn time at Port of Montreal using Discrete Event Simulation. Masters thesis, Concordia University.
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Abstract
Container ports are facing the growing problem of congestion due to the high volume of container trucks entering the terminal. Globalization, growth of trade and increasing consumer demand have further added to this complexity which has resulted in increased greenhouse gas emissions at the ports. Several measures are being undertaken by the ports to reduce this problem and improve port sustainability. Examples of these measures are implementing advanced technology equipment, implementing extended gate hours, changing the arrival patterns of trucks, and implementing variable gate lane policies.
The objective of the thesis is to develop a discrete event simulation (DES) model to investigate the congestion mitigation scenarios to improve terminal productivity and reduce truck turn times at the Port of Montreal. A case study with the Montreal Port Authority is conducted. The results of our simulation study yield upgrade of technology at the terminals as the best solution followed by managing the arrival patterns, changing gate lanes and extended gating hours. The proposed work is novel and one of the very few to be conducted in the context of Port of Montreal. The generated results can be used by decision makers at Port of Montreal in developing strategies to mitigate congestion and reduce truck turn times at terminals.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Alagesan, Vignesh |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Industrial Engineering |
Date: | 23 November 2017 |
Thesis Supervisor(s): | Awasthi, Anjali |
Keywords: | Discrete event simulation, Scenario analysis, Technology, Greenhouse gas emissions, Green harbor trucking, Congestion Mitigation. |
ID Code: | 983258 |
Deposited By: | Vignesh Alagesan |
Deposited On: | 11 Jun 2018 03:03 |
Last Modified: | 01 Jun 2020 00:00 |
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