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Water resources management under multi-parameter interactions: A factorial multi-stage stochastic programming approach

Listed author(s):
  • Zhou, Yang
  • Huang, Guo H.
  • Yang, Boting
Registered author(s):

    The paper proposes a factorial multi-stage stochastic programming (FMSP) approach to support water resources management under uncertainty. This approach was developed based on the conventional inexact multi-stage stochastic programming method. Five alternative inexact multi-stage stochastic programming algorithms in addition to the conventional algorithm were introduced and bundled to offer multiple decision options that reflect decision makers' perspectives and the complexities in system uncertainties. More importantly, factorial analysis, a multivariate inference method, was introduced into the modeling framework to analyze the potential interrelationships among a variety of uncertain parameters and their impacts on system performance. The proposed approach was applied to a water resources management case. The desired water-allocation schemes were obtained to assist in maximizing the total net benefit of the system. Multiple uncertain parameters and their interactions were examined, and those that had significant influences on system performance were identified. For example, the medium flow in the third planning period was the system objective's most influential factor. Any variation of this factor would significantly influence the acquisition of the total net benefit in the community. The significant interactions were also identified, such as the interaction between the agricultural sector's penalty and the medium flow in the third planning period. Through the analysis of multi-parameter interactions, the interrelationships among the uncertain parameters could be further revealed.

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    Article provided by Elsevier in its journal Omega.

    Volume (Year): 41 (2013)
    Issue (Month): 3 ()
    Pages: 559-573

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    Handle: RePEc:eee:jomega:v:41:y:2013:i:3:p:559-573
    DOI: 10.1016/
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    1. Huang, Guo H. & Baetz, Brian W. & Patry, Gilles G., 1995. "Grey integer programming: An application to waste management planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 83(3), pages 594-620, June.
    2. Nickel, Stefan & Saldanha-da-Gama, Francisco & Ziegler, Hans-Peter, 2012. "A multi-stage stochastic supply network design problem with financial decisions and risk management," Omega, Elsevier, vol. 40(5), pages 511-524.
    3. Maqsood, Imran & Huang, Guo H. & Scott Yeomans, Julian, 2005. "An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 208-225, November.
    4. Huang, G. H. & Baetz, B. W. & Patry, G. G., 1995. "Grey fuzzy integer programming: An application to regional waste management planning under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 17-38, March.
    5. Durbach, Ian N. & Stewart, Theodor J., 2012. "A comparison of simplified value function approaches for treating uncertainty in multi-criteria decision analysis," Omega, Elsevier, vol. 40(4), pages 456-464.
    6. Kreye, M.E. & Goh, Y.M. & Newnes, L.B. & Goodwin, P., 2012. "Approaches to displaying information to assist decisions under uncertainty," Omega, Elsevier, vol. 40(6), pages 682-692.
    7. Lin, Q.G. & Huang, G.H. & Bass, B. & Qin, X.S., 2009. "IFTEM: An interval-fuzzy two-stage stochastic optimization model for regional energy systems planning under uncertainty," Energy Policy, Elsevier, vol. 37(3), pages 868-878, March.
    8. Almiñana, M. & Escudero, L.F. & Landete, M. & Monge, J.F. & Rabasa, A. & Sánchez-Soriano, J., 2010. "WISCHE: A DSS for water irrigation scheduling," Omega, Elsevier, vol. 38(6), pages 492-500, December.
    9. Huang, G. H., 1998. "A hybrid inexact-stochastic water management model," European Journal of Operational Research, Elsevier, vol. 107(1), pages 137-158, May.
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