IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v26y2012i5p1183-1200.html
   My bibliography  Save this article

A Hybrid Dynamic Dual Interval Programming for Irrigation Water Allocation under Uncertainty

Author

Listed:
  • Lei Jin
  • Guohe Huang
  • Yurui Fan
  • Xianghui Nie
  • Guanhui Cheng

Abstract

Along with the economic development in Canada, the shortage of irrigation water has become a serious concern (Bouwer 1993 ; Hennessy 1993 ). In this study, a model of Dynamic Dual Interval Programming (DDIP) is developed and applied to the irrigation water allocation systems with uncertainty. DDIP method improves the existing dynamics interval programming by explicitly addressing the system uncertainties with a dual interval that had higher system reliability. The solution of DDIP is computationally effective, and its decision variables are incorporated into the solutions for final decision. In order to obtain the optimal allocation schemes in a dynamic process, the developed DDIP was applied to an irrigation water system. The results from this case study revealed that optimal solution can be obtained through the DDIP approach from the agriculture water management activities for feasible decisions. These decisions reflect the high uncertainty of the information in the boundaries of dual intervals. The solution presents a maximum benefit under limited yearly uncertain natural resources. Furthermore, the information obtained though this model may help the authority to make optimal decisions and to reduce the risk for uncertain situations. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • Lei Jin & Guohe Huang & Yurui Fan & Xianghui Nie & Guanhui Cheng, 2012. "A Hybrid Dynamic Dual Interval Programming for Irrigation Water Allocation under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(5), pages 1183-1200, March.
  • Handle: RePEc:spr:waterr:v:26:y:2012:i:5:p:1183-1200
    DOI: 10.1007/s11269-011-9953-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-011-9953-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11269-011-9953-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huang, G. H. & Baetz, B. W. & Patry, G. G., 1997. "A response to "A comment on 'Grey integer programming: An application to waste management planning under uncertainty"' by Larry Jenkins," European Journal of Operational Research, Elsevier, vol. 100(3), pages 638-641, August.
    2. 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.
    3. 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.
    4. Li, Y.F. & Huang, G.H. & Li, Y.P. & Xu, Y. & Chen, W.T., 2010. "Regional-scale electric power system planning under uncertainty--A multistage interval-stochastic integer linear programming approach," Energy Policy, Elsevier, vol. 38(1), pages 475-490, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shiang-Jen Wu & Jie-Sen Mai & Yi-Hong Lin & Keh-Chia Yeh, 2022. "Modeling Probabilistic-Based Reliability Analysis for Irrigation Water Supply Due to Uncertainties in Hydrological and Irrigation Factors," Sustainability, MDPI, vol. 14(19), pages 1-25, October.
    2. Jin, L. & Huang, G.H. & Fan, Y.R. & Wang, L. & Wu, T., 2015. "A pseudo-optimal inexact stochastic interval T2 fuzzy sets approach for energy and environmental systems planning under uncertainty: A case study for Xiamen City of China," Applied Energy, Elsevier, vol. 138(C), pages 71-90.
    3. Jingjing Wu & Jian Chen & Yu Han & Tongshu Li, 2020. "Study on Unsteady Flow Based on Optimized Water Distribution Model in Irrigation District," Sustainability, MDPI, vol. 12(4), pages 1-13, February.
    4. Elleuch, Mohamed Ali & Anane, Makram & Euchi, Jalel & Frikha, Ahmed, 2019. "Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case," Agricultural Systems, Elsevier, vol. 176(C).
    5. Kun Cheng & Qiang Fu & Xi Chen & Tianxiao Li & Qiuxiang Jiang & Xiaosong Ma & Ke Zhao, 2015. "Adaptive Allocation Modeling for a Complex System of Regional Water and Land Resources Based on Information Entropy and its Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 4977-4993, November.
    6. Mehran Homayounfar & Sai Lai & Mehdi Zommorodian & Amin Oroji & Arman Ganji & Sara Kaviani, 2015. "Developing a Non-Discrete Dynamic Game Model and Corresponding Monthly Collocation Solution Considering Variability in Reservoir Inflow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2599-2618, June.
    7. Gaiqiang Yang & Ping Guo & Mo Li & Shiqi Fang & Liudong Zhang, 2016. "An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 701-729, January.
    8. Galioto, Francesco & Battilani, Adriano, 2021. "Agro-economic simulation for day by day irrigation scheduling optimisation," Agricultural Water Management, Elsevier, vol. 248(C).
    9. Javier Alarcón & Alberto Garrido & Luis Juana, 2014. "Managing Irrigation Water Shortage: a Comparison Between Five Allocation Rules Based on Crop Benefit Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2315-2329, June.
    10. Yeonjoo Kim & Eun-Sung Chung & Sang-Mook Jun, 2015. "Iterative Framework for Robust Reclaimed Wastewater Allocation in a Changing Environment Using Multi-Criteria Decision Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(2), pages 295-311, January.
    11. Gaiqiang Yang & Ping Guo & Mo Li & Shiqi Fang & Liudong Zhang, 2016. "An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 701-729, January.
    12. Wen, Yeqiang & Shang, Songhao & Yang, Jian, 2017. "Optimization of irrigation scheduling for spring wheat with mulching and limited irrigation water in an arid climate," Agricultural Water Management, Elsevier, vol. 192(C), pages 33-44.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "An interval-valued minimax-regret analysis approach for the identification of optimal greenhouse-gas abatement strategies under uncertainty," Energy Policy, Elsevier, vol. 39(7), pages 4313-4324, July.
    2. Cao, M.F. & Huang, G.H. & Lin, Q.G., 2010. "Integer programming with random-boundary intervals for planning municipal power systems," Applied Energy, Elsevier, vol. 87(8), pages 2506-2516, August.
    3. Chen, C. & Li, Y.P. & Huang, G.H., 2016. "Interval-fuzzy municipal-scale energy model for identification of optimal strategies for energy management – A case study of Tianjin, China," Renewable Energy, Elsevier, vol. 86(C), pages 1161-1177.
    4. Hu, Qing & Huang, Guohe & Cai, Yanpeng & Huang, Ying, 2011. "Feasibility-based inexact fuzzy programming for electric power generation systems planning under dual uncertainties," Applied Energy, Elsevier, vol. 88(12), pages 4642-4654.
    5. Li, Y.F. & Li, Y.P. & Huang, G.H. & Chen, X., 2010. "Energy and environmental systems planning under uncertainty--An inexact fuzzy-stochastic programming approach," Applied Energy, Elsevier, vol. 87(10), pages 3189-3211, October.
    6. Natnael Nigussie Goshu & Surafel Luleseged Tilahun, 2016. "Grey theory to predict Ethiopian foreign currency exchange rate," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 2(2), pages 95-116.
    7. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2015. "A dynamic model to optimize municipal electric power systems by considering carbon emission trading under uncertainty," Energy, Elsevier, vol. 88(C), pages 636-649.
    8. Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.
    9. Chunguang Bai & Joseph Sarkis, 2013. "Green information technology strategic justification and evaluation," Information Systems Frontiers, Springer, vol. 15(5), pages 831-847, November.
    10. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    11. Lin, Q.G. & Huang, G.H., 2009. "A dynamic inexact energy systems planning model for supporting greenhouse-gas emission management and sustainable renewable energy development under uncertainty--A case study for the City of Waterloo,," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1836-1853, October.
    12. Tian, Chuyin & Huang, Guohe & Xie, Yulei, 2021. "Systematic evaluation for hydropower exploitation rationality in hydro-dominant area: A case study of Sichuan Province, China," Renewable Energy, Elsevier, vol. 168(C), pages 1096-1111.
    13. Zhou, Feng & Huang, Gordon H. & Chen, Guo-Xian & Guo, Huai-Cheng, 2009. "Enhanced-interval linear programming," European Journal of Operational Research, Elsevier, vol. 199(2), pages 323-333, December.
    14. Liang, M.S. & Huang, G.H. & Chen, J.P. & Li, Y.P., 2022. "Development of non-deterministic energy-water-carbon nexus planning model: A case study of Shanghai, China," Energy, Elsevier, vol. 246(C).
    15. Xu, Y. & Huang, G.H. & Qin, X.S. & Cao, M.F., 2009. "SRCCP: A stochastic robust chance-constrained programming model for municipal solid waste management under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 53(6), pages 352-363.
    16. Dong, C. & Huang, G.H. & Cai, Y.P. & Liu, Y., 2012. "An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city," Energy, Elsevier, vol. 37(1), pages 673-688.
    17. 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.
    18. Lv, Y. & Yan, X.D. & Sun, W. & Gao, Z.Y., 2015. "A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 188-199.
    19. Hsu, Chaug-Ing & Wen, Yuh-Horng, 2000. "Application of Grey theory and multiobjective programming towards airline network design," European Journal of Operational Research, Elsevier, vol. 127(1), pages 44-68, November.
    20. Mavrotas, George & Gakis, Nikos & Skoulaxinou, Sotiria & Katsouros, Vassilis & Georgopoulou, Elena, 2015. "Municipal solid waste management and energy production: Consideration of external cost through multi-objective optimization and its effect on waste-to-energy solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1205-1222.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:26:y:2012:i:5:p:1183-1200. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.