2026-09-19T02:20:49Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/356862026-06-06T01:06:38Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Henry S. Marcus.
Li, Xiaojing, S.M. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
2007-01-10T17:02:30Z
2007-01-10T17:02:30Z
2006
2006
http://hdl.handle.net/1721.1/35686
76893103
Thesis (S.M. in Ocean Systems Management)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006.
Includes bibliographical references (leaves 104-105).
Containership operators in the U.S. are confronted with a number of problems in the way they make critical fleet allocation decisions to meet the increase of shippers' demands. Instead of the empirical approach, this research describes an optimization method for the fleet allocation problem This methodology is applied by generating hypothetical values for a hypothetical firm. The endeavor of this method is to facilitate ship operations by allocating available fleet to maximize capacity and covering all the demands with the lowest cost The problem solving process is subdivided into three sub-models: the string simulation sub-model, the network design sub-model, and the fleet and cargo assignment sub-model. Each sub-model is explored by the combined approach of analysis and simulation, formulated as a Mixed Integer linear programming problem, implemented using the Optimization Programming language, and solved by CPLEX. This model provides several feasible fleet allocation proposals ranked by their profits, as well as yields the output of the detail cargo assignment at each port, the revenue, cost, and profit breakdown for each proposal.
(cont.) Subsequently, various scenarios can be studied in great detail by developing a User Interface in Java programming language based on a determined proposal. This interface allows the carrier to evaluate hundreds or thousands of fleet allocation scenarios and to quickly focus on key characteristics and options that are most relevant. This program extends the deterministic optimization method into a model supporting the solution to stochastic problems.
by Xiaojing Li.
S.M. in Transportation
S.M. in Ocean Systems Management
105 leaves
4831060 bytes
4835405 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Civil and Environmental Engineering.
Network design and fleet allocation model for vessel operation
Thesis
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<Abstract>Containership operators in the U.S. are confronted with a number of problems in the way they make critical fleet allocation decisions to meet the increase of shippers' demands. Instead of the empirical approach, this research describes an optimization method for the fleet allocation problem This methodology is applied by generating hypothetical values for a hypothetical firm. The endeavor of this method is to facilitate ship operations by allocating available fleet to maximize capacity and covering all the demands with the lowest cost The problem solving process is subdivided into three sub-models: the string simulation sub-model, the network design sub-model, and the fleet and cargo assignment sub-model. Each sub-model is explored by the combined approach of analysis and simulation, formulated as a Mixed Integer linear programming problem, implemented using the Optimization Programming language, and solved by CPLEX. This model provides several feasible fleet allocation proposals ranked by their profits, as well as yields the output of the detail cargo assignment at each port, the revenue, cost, and profit breakdown for each proposal.</Abstract>
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