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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.contributor.advisorRen, Jingzheng (ISE)en_US
dc.contributor.advisorLee, Carman (ISE)en_US
dc.contributor.advisorJi, Ping (ISE)en_US
dc.creatorLin, Ruojue-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/11456-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleLife cycle multi-criteria decision analysis for sustainability prioritization under multiple conditionsen_US
dcterms.abstractDue to the awareness of the contradiction between limited resources and the growing demand of humans, the concept of sustainability has been applied to major decisions more and more, especially those with long-term impacts. The variety of alternatives in a decision makes it difficult to figure out the best option, and it's necessary to establish efficient tools to assist sustainability-oriented decision making. Because Life Cycle Sustainability Assessment (LCSA) is a mature tool to scientifically quantify sustainability while multi-criteria decision analysis (MCDA) is an effective ranking method, a framework combining MCDA and LCSA provides a feasible and effective solution for sustainability-oriented prioritization problem. However, some complicated scenarios need to be studied cannot be solved by existing LCSA based MCDA methods. Therefore, a series of new methods dealing with multi-criteria prioritization problems for sustainability under complicated conditions needs to be developed. This study aims at developing a series of life cycle decision analysis methods for sustainability prioritization under complicated conditions. To deal with missing information, hybrid types of data, uncertainty, interdependent factors, opinions from multiple stakeholders, and index in form of efficiency, six LCSA-based MCDA methods for sustainability prioritization are proposed and validated. In this study, an improved grey relational analysis for hybrid and missing information (HM-GRA) model, a combination method of the z-number best-worst method (ZBWM) and the extended ELECTRE model, an improved interval goal programming method combining with a two-stage logarithmic goal programming (TLGP), a non-orthogonal coordinate system based TOPSIS (NOC-TOPSIS) model, a combination of FLLSM­FAHP and PROMETHEE model and interval slack-based measurement of super-efficiency (interval Super-SBM) model are proposed to deal with the complex scenarios mentioned above, respectively. This research analyzes the existing difficulties and problems of sustainability-oriented multi-criteria decision-making in complex scenarios. In addition, this study proposes innovative MCDA for sustainability prioritization with complicated conditions. These methods provide effective solutions for practical applications and provide new ideas for future research. Lastly, this research uses practical cases to demonstrate the proposed solutions. While verifying the feasibility of the alternatives in case studies, it also analyzes and puts forward insights for actual cases. Hence, this research also provides experts and policymakers with references and insights.en_US
dcterms.extentxix, 445 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2021en_US
dcterms.educationalLevelPh.D.en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHMultiple criteria decision makingen_US
dcterms.LCSHDecision makingen_US
dcterms.LCSHSustainabilityen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsopen accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/11456