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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorYuen, Kevin Kam Fung-
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleCognitive network process with fuzzy soft computing technique in collective decision aidingen_US
dcterms.abstractThe multi-criteria and multi-expert decision aiding models investigate the problems of identifying candidates, analyzing the criteria, and selecting the best alternative(s) based on the aggregation of the perceptions and preferences of the group decision makers. Although many studies have investigated these problems, there are no conclusions as to a single decision model that can dominate others. Among the various well-known models, the Analytic Hierarchy Process (AHP) /Analytic Network Process (ANP) is popular, and is applied in various domains, although there are some limitations. The Cognitive Network Process (CNP) is developed on the improvement of AHP/ANP with the cognitive decision process.en_US
dcterms.abstractThe CNP model is one of the models of the multi-criteria and multi-experts decision aiding. It applies the interdisciplinary techniques of decision sciences, cognitive sciences and fuzzy soft computing, on the basis of the mathematical modeling development. The cognitive architecture of the CNP is mainly comprised of five processes: Problem Cognition Process (PGP), Cognitive Assessment Process (CAP), Cognitive Prioritization Process (CPP), Multiple Information Fusion Process (MIP), and Decisional Volition Process (DVP). In PGP, decision problems are formed as a Structural Assessment Network (SAN). In CAP, a Compound Linguistic Ordinal Scale (CLOS) model is proposed for the improvement of rating activities of the assessment. In CPP, a Cognitive Prioritization Operator (CPO) of a Pairwise Opposite Matrix (POM) is proposed to derive the utility set from the POM. In MIP, a Cognitive Style and Aggregation Operator (CSAO) model is proposed for selection of aggregation operators to aggregate the utility sets with respect to the attitudes or cognitive styles of the decision makers. In DVP, a valuation function of the utility sets is used to provide the decision solution. The framework of CNP includes primitive and extent types. The primitive type is a individual decision making model using linguistic variables represented by crisp numbers. The extent types include the notions of the collective judgments and fuzzy linguistic variables.en_US
dcterms.abstractThe main contribution of the CNP includes the mathematical developments of CLOS, POM, CPO, CSAO, fuzzy POM, and fuzzy CPO. The numerical analyses with the discussions of these concepts are performed respectively. Five cases selected from other publications illustrate the usability and validity of the CNP, with comparisons with the (fuzzy) AHP/ANP, and complementation with other decision models.en_US
dcterms.abstractLike the impacts of AHP/ANP, the proposed CNP can be applied in many domains such as material management, transportation management, psychometrics, social sciences, business research, decision sciences, computer sciences, and engineering management. The CNP is the ideal alternative of the AHP/ANP.en_US
dcterms.extentxix, 432, 51 p. : ill. ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertations.en_US
dcterms.LCSHDecision making -- Methodology.en_US
dcterms.LCSHDecision making -- Mathematical models.en_US
dcterms.LCSHSoft computing.en_US
dcterms.accessRightsopen accessen_US

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