Applying queuing theory to the Port of Durban container terminal

dc.contributor.advisorAdendorff, Kris (Kristian)
dc.contributor.authorSchroder, Lothar
dc.date.accessioned2014-02-13T13:07:00Z
dc.date.available2014-02-13T13:07:00Z
dc.date.created2014-04-08
dc.date.issued2014
dc.descriptionDissertation (B.Eng. (Industrial and Systems Engineering))--University of Pretoria, 2014.en_US
dc.description.abstractThe content of the project report compiled in this document provides the reader with knowledge of operations at a container terminal and how a non-finite queueing theory model has been applied to the Port of Durban Container Terminal. The document initially discusses the general operations at a container terminal and type of equipment used and what their functions are. The document describes the specific operations at the two piers of the Port of Durban Container Terminal and at the Port of Rotterdam in the Netherlands. The Port of Rotterdam‟s Container Terminal operations serve as a benchmark to evaluate the Port of Durban Container Terminal operations. The main section of the report is a discussion on the non-finite queueing model which was created for the container terminal environment. The respective methods used and how the service and arrival rates of the model were established and calculated. The non-finite queueing model makes use of multi-server queueing theory and Jackson‟s rule to evaluate the models and calculate the total time a container has to wait in a queue for busy equipment, from when the container is unloaded from the sea vessel until it is stored in the stacking area. The aim of the model is to obtain the number of vehicles or equipment needed per quay crane to achieve a balanced system. A balanced system was defined as one where the least delays and congestion occur. The simulation model created in Simio was used to simulate the container terminal environment of the Port of Durban and the Port of Rotterdam container terminals. The aim of the simulation model was to obtain results from a different perspective. The simulation results are compared to the results of the queueing theory model, which are analysed, discussed and compared to a framework defined by a functionary from the container terminal environment. The end result was that the queueing theory model provided reliable results. The results for Pier 1 were that four truck-trailer units and four rubber tyre gantries should be assigned to a single quay crane. In the Pier 2 system, four straddle carriers should be assigned to a quay crane. iii The advantage of using the most balanced number of vehicles or equipment in the container terminal is that vessels can be processed faster, keeping customers satisfied and generating a greater profit.en_US
dc.description.availabilityunrestricteden_US
dc.description.departmentIndustrial and Systems Engineeringen_US
dc.identifier.citationSchroder, L 2014, Applying queuing theory to the Port of Durban container terminal, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/33480>
dc.identifier.urihttp://hdl.handle.net/2263/33480
dc.language.isoenen_US
dc.rights© 2014 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoriaen_US
dc.subjectQueuing theoryen_US
dc.subjectSimulation modellingen_US
dc.subjectContainer terminalen_US
dc.titleApplying queuing theory to the Port of Durban container terminalen_US
dc.typeMini Dissertationen_US

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