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Inexact de Novo programming for water resources systems planning

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  • Zhang, Y.M.
  • Huang, G.H.
  • Zhang, X.D.

Abstract

This study presents an interval de Novo programming (IDNP) approach for the design of optimal water-resources-management systems under uncertainty. The model is derived by incorporating the existing interval programming and de Novo programming, allowing uncertainties represented as intervals within the optimization framework. The developed IDNP approach has the advantages in constructing optimal system design via an ideal system by introducing the flexibility toward the available resources in the system constraints. A simple numerical example is introduced to illustrate the IDNP approach. The IDNP is then applied to design an inexact optimal system with budget limit instead of finding the optimum in a given system with fixed resources in a water resources planning case. The results demonstrate that the developed method efficiently produces stable solutions under different objectives. Optimal supplies of good-quality water are obtained in considering different revenue targets of municipal-industrial-agricultural competition under a given budget.

Suggested Citation

  • Zhang, Y.M. & Huang, G.H. & Zhang, X.D., 2009. "Inexact de Novo programming for water resources systems planning," European Journal of Operational Research, Elsevier, vol. 199(2), pages 531-541, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:2:p:531-541
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    References listed on IDEAS

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    1. 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.
    2. Zeleny, Milan, 1986. "Optimal system design with multiple criteria: De Novo programming approach," Engineering Costs and Production Economics, Elsevier, vol. 10(2), pages 89-94, June.
    3. Yong Shi, 1999. "Optimal System Design with Multiple Decision Makers and Possible Debt: A Multicriteria De Novo Programming Approach," Operations Research, INFORMS, vol. 47(5), pages 723-729, October.
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    Cited by:

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    2. Zhang, Xiaodong & Duncan, Ian J. & Huang, Gordon & Li, Gongchen, 2014. "Identification of management strategies for CO2 capture and sequestration under uncertainty through inexact modeling," Applied Energy, Elsevier, vol. 113(C), pages 310-317.
    3. Zhang, Xiaodong & Huang, Guo H. & Nie, Xianghui, 2009. "Optimal decision schemes for agricultural water quality management planning with imprecise objective," Agricultural Water Management, Elsevier, vol. 96(12), pages 1723-1731, December.
    4. Zhang, Yi Mei & Huang, Guo He, 2011. "Inexact credibility constrained programming for environmental system management," Resources, Conservation & Recycling, Elsevier, vol. 55(4), pages 441-447.
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    6. Li, Zhong & Huang, Gordon & Zhang, Yimei & Li, Yongping, 2013. "Inexact two-stage stochastic credibility constrained programming for water quality management," Resources, Conservation & Recycling, Elsevier, vol. 73(C), pages 122-132.
    7. Nurullah Umarusman, 2018. "Fuzzy Goal Programming Problem Based on Minmax Approach for Optimal System Design," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 6(1), pages 177-192, June.

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