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Please use this identifier to cite or link to this item: http://hdl.handle.net/10625/47909

Title: Robust stochastic fuzzy possibilistic programming for environmental decision making under uncertainty
Authors: Zhang, Xiaodong
Huang, Guo H.
Nie, Xianghui
Keywords: FUZZY POSSIBILISTIC PROGRAMMING
ROBUST
CHANCE-CONSTRAINED
WATER QUALITY MANAGEMENT
DECISION MAKING
UNCERTAINTY
SUB-SAHARAN AFRICA
GLOBAL
ASIA
URBAN WATER AND SANITATION
WATER RESOURCES MANAGEMENT
NON-POINT SOURCE POLLUTION
WATER POLLUTION
Issue Date: 2009
Publisher: Elsevier
Abstract: Nonpoint source (NPS) water pollution is one of serious environmental issues, especially within an agricultural system. This study aims to propose a robust chance-constrained fuzzy possibilistic programming (RCFPP) model for water quality management within an agricultural system, where solutions for farming area, manure/fertilizer application amount, and livestock husbandry size under different scenarios are obtained and interpreted. Through improving upon the existing fuzzy possibilistic programming, fuzzy robust programming and chance-constrained programming approaches, the RCFPP can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original fuzzy constraints, the RCFPP enhances the robustness of the optimization processes and resulting solutions. The results of the case study indicate that useful information can be obtained through the proposed RCFPP model for providing feasible decision schemes for different agricultural activities under different scenarios (combinations of different p-necessity and pi levels). A p-necessity level represents the certainty or necessity degree of the imprecise objective function, while a pi level means the probabilities at which the constraints will be violated. A desire to acquire high agricultural income would decrease the certainty degree of the event that maximization of the objective be satisfied, and potentially violate water management standards; willingness to accept low agricultural income will run into the risk of potential system failure. The decision variables under combined p-necessity and pi levels were useful for the decision makers to justify and/or adjust the decision schemes for the agricultural activities through incorporation of their implicit knowledge. The results also suggest that this developed approach is applicable to many practical problems where fuzzy and probabilistic distribution information simultaneously exist
URI: http://hdl.handle.net/10625/47909
ISSN: 0048-9697
Project Number: 103710
Project Title: ECOPOLIS Graduate Research and Design Competition (Global)
Document Delivery: To enquire about document delivery, contact the IDRC Library : reference@idrc.ca or 613-696-2578 / Pour plus de renseignements sur la livraison de documents, communiquer avec la bibliothèque du CRDI : reference@idrc.ca ou 613-696-2578.
Appears in Collections:IDRC Research Results / Résultats de recherches du CRDI
Research Results (AFS) / Résultats de recherche (ASA)

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