Fuzzy ranking from fuzzy pairwise comparisons with applications

dc.contributor.authorWang, Yunfeng
dc.date.accessioned2015-09-16T17:08:23Z
dc.date.available2015-09-16T17:08:23Z
dc.date.issued2015-08
dc.descriptionA Thesis Submitted in Partial fulfillment of the Requirements for Degree of MASTER OF SCIENCE in The Graduate Mathematics Program in Applied and Computational Mathematics Option from Texas A&M University-Corpus Christi in Corpus Christi, Texas.en_US
dc.description.abstractOne method of ranking items is to score all of them against a standard scale. Sometimes it is difficult to create or use such a scale. As an alternative, it is possible to make side-by-side comparisons of some or all of the pairs of items. Then the problem is to convert the collective pairwise comparisons into a ranking. This problem has been studied previously in many contexts. This thesis addresses several methods, including where fuzzy comparisons are made for some, but not all, of the pairs. The Colley method and PageRank algorithm both use pairwise comparisons for some pairs to rank all items in a set. This thesis shows how those pairwise comparisons can be fuzzy. It also shows how Saaty's method for ranking alternatives can be completed when not all comparisons are used.en_US
dc.description.collegeCollege of Science and Engineeringen_US
dc.description.departmentMathematics and Statisticsen_US
dc.identifier.urihttp://hdl.handle.net/1969.6/641
dc.language.isoen_USen_US
dc.rightsThis material is made available for use in research, teaching, and private study, pursuant to U.S. Copyright law. The user assumes full responsibility for any use of the materials, including but not limited to, infringement of copyright and publication rights of reproduced materials. Any materials used should be fully credited with its source. All rights are reserved and retained regardless of current or future development or laws that may apply to fair use standards. Permission for publication of this material, in part or in full, must be secured with the author and/or publisher.en_US
dc.subjectFuzzy Rankingen_US
dc.subjectPairwise Comparisonen_US
dc.subjectIncomplete Matrixen_US
dc.titleFuzzy ranking from fuzzy pairwise comparisons with applicationsen_US
dc.typeTexten_US
dc.type.genreThesisen_US
thesis.degree.disciplineMathematicsen_US
thesis.degree.grantorTexas A & M University--Corpus Christien_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US

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