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Multi-objective constrained optimization for decision making and optimization for system architectures

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dc.contributor.advisor Edward F. Crawley and Brian C. Williams. en_US
dc.contributor.author Lin, Maokai en_US
dc.contributor.other Massachusetts Institute of Technology. Computation for Design and Optimization Program. en_US
dc.date.accessioned 2010-09-02T14:57:12Z
dc.date.available 2010-09-02T14:57:12Z
dc.date.copyright 2010 en_US
dc.date.issued 2010 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/58188
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 171-174). en_US
dc.description.abstract This thesis proposes new methods to solve three problems: 1) how to model and solve decision-making problems, 2) how to translate between a graphical representation of systems and a matrix representation of systems, and 3) how to cluster single and multiple Design Structure Matrices (DSM). To solve the first problem, the thesis provides an approach to model decisionmaking problems as multi-objective Constraint Optimization Problems (COP) based on their common structures. A set of new algorithms to find Pareto front of multi objective COP is developed by generalizing upon the Conflict-directed A* (CDA*) algorithm for single-objective COPs. Two case studies - Apollo mission mode study and earth science decadal survey study - are provided to demonstrate the effectiveness of the modelling approach and the set of algorithms when they are applied to real world problems. For the second problem, the thesis first extends classical DSMs to incorporate different relations between components in a system. The Markov property of the extended DSM is then revealed. Furthermore, the thesis introduces the concept of "projection", which maps and condenses a system graph to a DSM based on the Markov property of DSM. For the last problem, an integer programming model is developed to encode the single DSM clustering problem. The thesis tests the effectiveness of the model by applying it to a part of a real-world jet engine design project. The model is further extended to solve the multiple DSM clustering problems. en_US
dc.description.statementofresponsibility by Maokai Lin. en_US
dc.format.extent 174 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Computation for Design and Optimization Program. en_US
dc.title Multi-objective constrained optimization for decision making and optimization for system architectures en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Computation for Design and Optimization Program. en_US
dc.identifier.oclc 640140593 en_US


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