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dc.contributor.advisorKlein, Cerry M.eng
dc.contributor.authorLi, Wei, 1982-eng
dc.date.issued2007eng
dc.date.submitted2007 Springeng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on November 9, 2007)eng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionThesis (M.S.) University of Missouri-Columbia 2007.eng
dc.descriptionDissertations, Academic -- University of Missouri--Columbia -- Industrial engineering.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] In Multi-Attribute Decision Making (MADM) problems, several methods have been developed to aid the decision maker. MADM procedures can be applied to a wide range of human choices, from the professional to the managerial to the political. In reality, SAW and AHP are the two best known and widely used approaches to determine the order or preference of various alternatives. Other methods such as DI, TOPSIS, and WPM are also well-known in MADM research field. Most of the models assume independence among attributes. AHP and DI are two models that claim to work regardless of dependency among attributes, while some claim that dependency does not have significant impact on results. The question though is whether dependency has any impact on decision quality in practice. In this research, we generate data with given levels of dependency and apply selected MADM methods to the data. By comparing the results from these methods, we hope to determine whether dependency among attributes has an impact on the ranking alternatives or not. It should be noted that AHP has a different approach that it does not share the same raw data as other methods so it won't be included in our simulation experiment.eng
dc.identifier.merlinb61280008eng
dc.identifier.oclc181026167eng
dc.identifier.urihttps://hdl.handle.net/10355/5989
dc.identifier.urihttps://doi.org/10.32469/10355/5989eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campus of the University of Missouri--Columbia.eng
dc.subject.lcshDecision makingeng
dc.subject.lcshIndustrial management -- Decision makingeng
dc.subject.lcshAttribute (Philosophy)eng
dc.subject.lcshDependency (Psychology)eng
dc.titleMulti-attribute decision making: a test on the impact of data attributes dependencyeng
dc.typeThesiseng
thesis.degree.disciplineIndustrial engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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