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Robustness-Optimality Tradeoff for Watershed Load Reduction Decision Making under Deep Uncertainty

Author

Listed:
  • Han Su

    (Peking University)

  • Feifei Dong

    (Peking University)

  • Yong Liu

    (Peking University)

  • Rui Zou

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

  • Huaicheng Guo

    (Peking University)

Abstract

Practical and optimal reduction of watershed loads under deep uncertainty requires sufficient search alternatives and direct evaluation of robustness. These requirements contribute to the understanding of the tradeoff between cost and robustness; while they are not well addressed in previous studies. This study thereby (a) uses preconditioning technique in Evolutionary Algorithm to reduce unnecessary search space, which enables a sufficient search; and (b) derives Robustness Index (RI) as a second-tier optimization objective function to achieve refined solutions (solved by GA) that address both robustness and optimality. Uncertainty-based Refined Risk Explicit Linear Interval Programming is used to generate alternatives (solved by Controlled elitist NSGA-II). The robustness calculation error is also quantified. Proposed approach is applied to Lake Dianchi, China. Results demonstrate obvious improvement in robustness after conducting sufficient search and negative robustness-optimality trade-offs, and provides a detailed characteristic of robustness that can serve as references for decision-making.

Suggested Citation

  • Han Su & Feifei Dong & Yong Liu & Rui Zou & Huaicheng Guo, 2017. "Robustness-Optimality Tradeoff for Watershed Load Reduction Decision Making under Deep Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3627-3640, September.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:11:d:10.1007_s11269-017-1689-3
    DOI: 10.1007/s11269-017-1689-3
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    References listed on IDEAS

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    1. Goberna, M.A. & Jeyakumar, V. & Li, G. & Vicente-Pérez, J., 2015. "Robust solutions to multi-objective linear programs with uncertain data," European Journal of Operational Research, Elsevier, vol. 242(3), pages 730-743.
    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. A. L. Soyster, 1973. "Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming," Operations Research, INFORMS, vol. 21(5), pages 1154-1157, October.
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