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dc.contributor.advisorHenry S. Marcus.en_US
dc.contributor.authorLi, Xiaojing, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.en_US
dc.date.accessioned2007-01-10T17:02:30Z
dc.date.available2007-01-10T17:02:30Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/35686
dc.descriptionThesis (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.en_US
dc.descriptionIncludes bibliographical references (leaves 104-105).en_US
dc.description.abstractContainership 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.en_US
dc.description.abstract(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.en_US
dc.description.statementofresponsibilityby Xiaojing Li.en_US
dc.format.extent105 leavesen_US
dc.format.extent4831060 bytes
dc.format.extent4835405 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectMechanical Engineering.en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleNetwork design and fleet allocation model for vessel operationen_US
dc.typeThesisen_US
dc.description.degreeS.M.in Transportationen_US
dc.description.degreeS.M.in Ocean Systems Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc76893103en_US


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