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Uncertainty-Based Multi-Objective Decision Making with Hierarchical Reliability Analysis Under Water Resources and Environmental Constraints

Author

Listed:
  • Feifei Dong

    (Peking University)

  • Yong Liu

    (Peking University)

  • Han Su

    (Peking University)

  • Zhongyao Liang

    (Peking University)

  • Rui Zou

    (Tetra Tech, Inc
    Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed)

  • Huaicheng Guo

    (Peking University)

Abstract

Rapid urbanization and population growth have resulted in worldwide serious water shortage and environmental deterioration. It is then essential for efficient and feasible allocation of scarce water and environment resources to the competing users. Due to inherent uncertainties, decision making for resources allocation is vulnerable to failure. The scheme feasibility can be evaluated by reliability, representing the failure probability. A progressive reliability-oriented multi-objective (PROMO) optimal decision-making procedure is proposed in this study to deal with problems with numerous reliability objectives. Dimensionality of the objectives is reduced by a top-down hierarchical reliability analysis (HRA) process combining optimization with evaluation. Pareto solutions of the reformulated model, representing alternative schemes non-dominated with each other, are generated by a metalmodel-based optimization algorithm. Evaluation and identification of Pareto solutions are conducted by multi-criteria decision analysis (MCDA). The PROMO procedure is demonstrated for a case study on industrial structure transformation under strict constraints of water resources and total environmental emissions amounts in Guangzhou City, South China. The Pareto front reveals tradeoffs between economic returns of the industries and system reliability. For different reliability preference scenarios, the Pareto solutions are ranked and the top-rated one was recommended for implementation. The model results indicate that the PROMO procedure is effective for model solving and scheme selection of uncertainty-based multi-objective decision making.

Suggested Citation

  • Feifei Dong & Yong Liu & Han Su & Zhongyao Liang & Rui Zou & Huaicheng Guo, 2016. "Uncertainty-Based Multi-Objective Decision Making with Hierarchical Reliability Analysis Under Water Resources and Environmental Constraints," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 805-822, January.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:2:d:10.1007_s11269-015-1192-7
    DOI: 10.1007/s11269-015-1192-7
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    References listed on IDEAS

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    1. X. Qin & G. Huang, 2009. "An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 661-695, March.
    2. Mahdi Zarghami & Nasim Safari & Ferenc Szidarovszky & Shafiqul Islam, 2015. "Nonlinear Interval Parameter Programming Combined with Cooperative Games: a Tool for Addressing Uncertainty in Water Allocation Using Water Diplomacy Framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4285-4303, September.
    3. Reza Hajiabadi & Mahdi Zarghami, 2014. "Multi-Objective Reservoir Operation with Sediment Flushing; Case Study of Sefidrud Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5357-5376, December.
    4. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    5. Thomas L. Saaty, 2005. "The Analytic Hierarchy and Analytic Network Processes for the Measurement of Intangible Criteria and for Decision-Making," International Series in Operations Research & Management Science, in: Multiple Criteria Decision Analysis: State of the Art Surveys, chapter 0, pages 345-405, Springer.
    6. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.
    7. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
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