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dc.contributor.authorDuan, Yuqing-
dc.description.abstractPairwise comparisons matrices (PCM) are commonly used when different entities or abstract concepts are compared for making decisions. The compared entities for decision making can be both subjective and objective indicators. The elements in PCM are ratios in case of multiplicative version. Using differential evolution (DE) heuristic algorithm, we can find an optimal solution for a given PCM. The optimization results are fairly good with geometric mean (GM) and eigenvector (EV). The thesis provides an introduction of differential evolution and how to apply it to the global optimization of PC matrices. IDEs and Java/R packages used in the Monte Carlo experiment will be discussed. Some results of considerable importance for PC matrices that have been obtained will also be illustrated in the thesis.en_US
dc.subjectPairwise comparisons matricesen_US
dc.subjectdifferential evolution heuristicen_US
dc.subjectgeometric meanen_US
dc.subjectMonte Carlo experimenten_US
dc.subjectJava, R.en_US
dc.titleGlobal 0ptimization of pairwise comparisons matrix based on differential evolution algorithmen_US
dc.description.degreeMaster of Science (MSc) in Computational Sciencesen_US
dc.publisher.grantorLaurentian University of Sudburyen_US
Appears in Collections:Computational Sciences - Master's theses
Master's Theses

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