IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v30y2016i2p701-729.html
   My bibliography  Save this article

An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem

Author

Listed:
  • Gaiqiang Yang
  • Ping Guo
  • Mo Li
  • Shiqi Fang
  • Liudong Zhang

Abstract

In this study, an improved single-step method (SSM) is developed based on two-step method (TSM) to solve the interval-parameter linear programming (ILP) model of which the right-hand sides are highly uncertain. Two numerical examples are presented to ascertain appropriate value of λ in SSM. The risk preference degree of λ could be 0.8 for maximum objective function type. To demonstrate the applicability of the developed method, an agricultural water management problem has been provided in the case study section. The results show that SSM is more effective than TSM for complete solutions. There is only partial solution obtained from the first submodel of TSM, because the right-hand side of the wheat output constraint is highly uncertain. Finally, local farmers’ net benefit reaches to [8.949, 12.442] × 10 8 RMB (the unit of Chinese currency). The priority order of crops that are needed to be irrigated by surface water is maize > wheat > cotton. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • 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.
  • Handle: RePEc:spr:waterr:v:30:y:2016:i:2:p:701-729
    DOI: 10.1007/s11269-015-1186-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-015-1186-5
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11269-015-1186-5?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. Kim, H.K. & Jang, T.I. & Im, S.J. & Park, S.W., 2009. "Estimation of irrigation return flow from paddy fields considering the soil moisture," Agricultural Water Management, Elsevier, vol. 96(5), pages 875-882, May.
    2. Ye Liu & Guohe Huang & Yanpeng Cai & Cong Dong, 2011. "An Inexact Mix-Integer Two-Stage Linear Programming Model for Supporting the Management of a Low-Carbon Energy System in China," Energies, MDPI, vol. 4(10), pages 1-30, October.
    3. 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.
    4. 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.
    5. 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.
    6. Yang, Gaiqiang & Guo, Ping & Huo, Lijuan & Ren, Chongfeng, 2015. "Optimization of the irrigation water resources for Shijin irrigation district in north China," Agricultural Water Management, Elsevier, vol. 158(C), pages 82-98.
    7. Q. Lin & G. Huang, 2011. "Interval-fuzzy stochastic optimization for regional energy systems planning and greenhouse-gas emission management under uncertainty—a case study for the Province of Ontario, Canada," Climatic Change, Springer, vol. 104(2), pages 353-378, January.
    8. 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.
    9. J W Chinneck & K Ramadan, 2000. "Linear programming with interval coefficients," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(2), pages 209-220, February.
    10. Lin, Q.G. & Huang, G.H., 2010. "An inexact two-stage stochastic energy systems planning model for managing greenhouse gas emission at a municipal level," Energy, Elsevier, vol. 35(5), pages 2270-2280.
    11. D. Fu & Y. Li & G. Huang, 2013. "A Factorial-based Dynamic Analysis Method for Reservoir Operation Under Fuzzy-stochastic Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4591-4610, October.
    12. P. Guo & G. Huang & L. He & H. Zhu, 2009. "Interval-parameter Two-stage Stochastic Semi-infinite Programming: Application to Water Resources Management under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(5), pages 1001-1023, March.
    13. M. Li & P. Guo & G. Yang & S. Fang, 2014. "IB-ICCMSP: An Integrated Irrigation Water Optimal Allocation and Planning Model Based on Inventory Theory under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 241-260, 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. Zhang, Chenglong & Li, Xuemin & Guo, Ping & Huo, Zailin, 2021. "Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty," Agricultural Water Management, Elsevier, vol. 254(C).
    2. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong, 2018. "An interval multi-objective programming model for irrigation water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 196(C), pages 24-36.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. Niknam, Taher & Narimani, Mohammad rasoul & Jabbari, Masoud & Malekpour, Ahmad Reza, 2011. "A modified shuffle frog leaping algorithm for multi-objective optimal power flow," Energy, Elsevier, vol. 36(11), pages 6420-6432.
    8. 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.
    9. Figueroa–García, Juan Carlos & Hernández, Germán & Franco, Carlos, 2022. "A review on history, trends and perspectives of fuzzy linear programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    10. Chen, Yizhong & Lu, Hongwei & Li, Jing & Huang, Guohe & He, Li, 2016. "Regional planning of new-energy systems within multi-period and multi-option contexts: A case study of Fengtai, Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 356-372.
    11. Li, G.C. & Huang, G.H. & Lin, Q.G. & Zhang, X.D. & Tan, Q. & Chen, Y.M., 2011. "Development of a GHG-mitigation oriented inexact dynamic model for regional energy system management," Energy, Elsevier, vol. 36(5), pages 3388-3398.
    12. Li, M.W. & Li, Y.P. & Huang, G.H., 2011. "An interval-fuzzy two-stage stochastic programming model for planning carbon dioxide trading under uncertainty," Energy, Elsevier, vol. 36(9), pages 5677-5689.
    13. Mandal, Uday & Dhar, Anirban & Panda, Sudhindra N., 2021. "Enhancement of sustainable agricultural production system by integrated natural resources management framework under climatic and operational uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).
    14. H. Mishmast Nehi & H. A. Ashayerinasab & M. Allahdadi, 2020. "Solving methods for interval linear programming problem: a review and an improved method," Operational Research, Springer, vol. 20(3), pages 1205-1229, September.
    15. Zhou, Yang & Huang, Guo H. & Yang, Boting, 2013. "Water resources management under multi-parameter interactions: A factorial multi-stage stochastic programming approach," Omega, Elsevier, vol. 41(3), pages 559-573.
    16. 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.
    17. 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.
    18. Chunguang Bai & Joseph Sarkis, 2013. "Green information technology strategic justification and evaluation," Information Systems Frontiers, Springer, vol. 15(5), pages 831-847, November.
    19. 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.
    20. 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.

    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:30:y:2016:i:2:p:701-729. 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.