Measuring the capacity of a port system : a case study on a Southeast Asian port
Author(s)Salminen, Jason Bryan
Massachusetts Institute of Technology. Engineering Systems Division.
James B. Rice Jr. and Ioannis N. Lagoudis.
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As economies develop and trade routes change, investment in port infrastructure is essential to maintain the necessary capacity for an efficiently functioning port system and to meet expected demand for all types of cargo. However, these largescale, expensive investments in long-term infrastructure assets must be made despite a variety of future uncertainties that may potentially influence a port's performance. By using a Southeast Asian multi-purpose port as a case study, this thesis paper enhances the investment decision-making process for port infrastructure through the successful application and modification of two existing methodologies and the development of both an investment tool and a framework for selecting an optimal investment strategy to address capacity constraints within a port system. Applied at the case study port, the research evaluates a modification of an existing methodology for the measurement of port capacity, developed by Lagoudis and Rice, to identify bottlenecks within the port system. The research then examines a modification of an existing methodology, developed by de Neufville and Scholtes, for the evaluation of potential investment strategies under uncertainty. A simulation screening model is developed to forecast expected profitability under uncertainty for potential investment strategies, including strategies with flexible options, and to determine the optimal strategy. The thesis concludes with the presentation of a decision-making process for port infrastructure investment and recommended refinements to the existing methodologies.
Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 172-177).
DepartmentMassachusetts Institute of Technology. Engineering Systems Division.; Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology
Engineering Systems Division.