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dc.contributor.advisorHuang, Guo H.
dc.contributor.authorChen, Xiujuan
dc.date.accessioned2014-10-20T20:25:39Z
dc.date.available2014-10-20T20:25:39Z
dc.date.issued2014-04
dc.identifier.urihttp://hdl.handle.net/10294/5494
dc.descriptionA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Environmental Systems Engineering, University of Regina. x, 186 p.en_US
dc.description.abstractWith the population growth and the increase of waste generation throughout the world, municipal solid waste (MSW) management has become a critical issue for urban environment. Numerous factors, such as shrinking waste disposal capacities, increasing environmental and health concerns, and varying legislative and political conditions, influence the planning of MSW management in the real world. When planning MSW management, the problems of waste-flow allocation and waste inventory should be addressed by waste managers. Moreover, various uncertainties exist in these problems and may be further intensified due to complex features of the system components. Therefore, in response to these challenges, effective approaches are desired for MSW management planning. In this research, an inexact inventory-theory-based chance-constrained programming (IICP) model was proposed for the planning of MSW management systems. The IICP model was derived through introducing the inventory theory into an inexact chance-constrained programming (ICP) framework. Not only could the uncertainties presented as probability distributions and interval values be addressed, but also the waste inventory problems of MSW management could be solved. Solutions including total waste flow, waste-transfer batch size, and the duration between waste transfer events (DWTE) were obtained. Analyses of the tradeoff between system cost and constraint-violation risk were also undertaken. Moreover, compared to the ICP model, the IICP model could more accurately reflect the complexity of the MSW management system and provide more reasonable information for decision makers. In addition, based on the IICP model, an inexact inventory-theory-based waste management planning (IIWMP) model was developed and applied to support long-term planning of the MSW management system in the City of Xiamen, the special economic zone of the Fujian, China. In the IIWMP model, the techniques of inventory model, inexact chance-constrained programming, interval-valued fuzzy linear-programming, and mixed-integer linear programming were integrated. Multiple uncertainties that existed in Xiamen’s MSW management systems were addressed in association with the complexities of waste inventory. Decision alternatives for waste allocation and capacity expansion with minimized system cost under different risk levels were provided for the MSW management in the City of Xiamen. The results indicated that the developed model was useful for identifying desired waste management policies under various uncertainties.en_US
dc.language.isoenen_US
dc.publisherFaculty of Graduate Studies and Research, University of Reginaen_US
dc.titleInexact Inventory-Theory-Based Mathematical Programming For Municipal Solid Waste Management Under Multiple Uncertaintiesen_US
dc.typeThesisen
dc.description.authorstatusStudenten
dc.description.peerreviewyesen
thesis.degree.nameMaster of Applied Science (MASc)en_US
thesis.degree.levelMaster'sen
thesis.degree.disciplineEngineering - Environmental Systemsen_US
thesis.degree.grantorUniversity of Reginaen
thesis.degree.departmentFaculty of Engineering and Applied Scienceen_US
dc.contributor.committeememberAzam, Shahid
dc.contributor.committeememberDeng, Dianliang
dc.contributor.externalexaminerZeng, Fanhua
dc.identifier.tcnumberTC-SRU-5494
dc.identifier.thesisurlhttp://ourspace.uregina.ca/bitstream/handle/10294/5494/Chen_Xiujuan_200314297_MASC_EVSE_Spring2014.pdf


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