IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v26y2012i7p2015-2038.html
   My bibliography  Save this article

Identifying Optimal Water Resources Allocation Strategies through an Interactive Multi-Stage Stochastic Fuzzy Programming Approach

Author

Listed:
  • S. Wang
  • G. Huang

Abstract

In this study, an interactive multi-stage stochastic fuzzy programming (IMSFP) approach has been developed through incorporating an interactive fuzzy resolution (IFR) method within an inexact multi-stage stochastic programming framework. IMSFP can deal with dual uncertainties expressed as fuzzy boundary intervals that exist in the objective function and the left- and right-hand sides of constraints. Moreover, IMSFP is capable of reflecting dynamics of uncertainties and the related decision processes through constructing a set of representative scenarios within a multi-stage context. A management problem in terms of water resources allocation has been studied to illustrate applicability of the proposed approach. The results indicate that a set of solutions under different feasibility degrees (i.e., risk of constraint violation) has been generated for planning the water resources allocation. They can not only help quantify the relationship between the objective-function value and the risk of violating the constraints, but also enable decision makers (DMs) to identify, in an interactive way, a desired compromise between two factors in conflict: satisfaction degree of the goal and feasibility degree of constraints. Besides, a number of decision alternatives have been generated under different policies for water resources management, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised water-allocation targets are violated, and thus help DMs to identify desired water-allocation schemes under uncertainty. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • S. Wang & G. Huang, 2012. "Identifying Optimal Water Resources Allocation Strategies through an Interactive Multi-Stage Stochastic Fuzzy Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 2015-2038, May.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:7:p:2015-2038
    DOI: 10.1007/s11269-012-9996-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-012-9996-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-012-9996-1?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. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. 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.
    3. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    4. P. Jairaj & S. Vedula, 2000. "Multireservoir System Optimization using Fuzzy Mathematical Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 14(6), pages 457-472, December.
    5. Huang, G. H., 1998. "A hybrid inexact-stochastic water management model," European Journal of Operational Research, Elsevier, vol. 107(1), pages 137-158, May.
    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. Pingale, Santosh M. & Jat, Mahesh K. & Khare, Deepak, 2014. "Integrated urban water management modelling under climate change scenarios," Resources, Conservation & Recycling, Elsevier, vol. 83(C), pages 176-189.
    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. Galioto, F., 2018. "The value of information for the management of water resources in agriculture: comparing the economic impact of alternative sources of information to schedule irrigation," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277384, International Association of Agricultural Economists.
    4. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
    5. Jing Tian & Shenglian Guo & Dedi Liu & Zhengke Pan & Xingjun Hong, 2019. "A Fair Approach for Multi-Objective Water Resources Allocation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3633-3653, August.
    6. Wang, S. & Huang, G.H., 2014. "An integrated approach for water resources decision making under interactive and compound uncertainties," Omega, Elsevier, vol. 44(C), pages 32-40.
    7. J. Alarcón & L. Juana, 2016. "The Water Markets as Effective Tools of Managing Water Shortages in an Irrigation District," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2611-2625, June.
    8. Xiaona Li & Xiaosheng Wang & Haiying Guo & Weimin Ma, 2020. "Multi-Water Resources Optimal Allocation Based on Multi-Objective Uncertain Chance-Constrained Programming Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 4881-4899, December.
    9. Wang, S. & Huang, G.H., 2016. "Risk-based factorial probabilistic inference for optimization of flood control systems with correlated uncertainties," European Journal of Operational Research, Elsevier, vol. 249(1), pages 258-269.
    10. Wang, S. & Huang, G.H., 2015. "A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management," European Journal of Operational Research, Elsevier, vol. 240(2), pages 572-581.
    11. 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.
    12. Zhao, Siwei & Liu, Weidong & Zhu, Mengyuan & Ma, Yanfang & Li, Zongmin, 2021. "A priority-based multi-objective framework for water resources diversion and allocation in the middle route of the South-to-North Water Diversion Project," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    13. Galioto, Francesco & Chatzinikolaou, Parthena & Raggi, Meri & Viaggi, Davide, 2020. "The value of information for the management of water resources in agriculture: Assessing the economic viability of new methods to schedule irrigation," Agricultural Water Management, Elsevier, vol. 227(C).

    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. 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.
    2. Mike Spiliotis & Dionissis Latinopoulos & Lampros Vasiliades & Kyriakos Rafailidis & Eleni Koutsokera & Ifigenia Kagalou, 2022. "Flexible Goal Programming for Supporting Lake Karla’s (Greece) Sustainable Operation," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    3. Li, Y.P. & Huang, G.H. & Yang, Z.F. & Nie, S.L., 2008. "IFMP: Interval-fuzzy multistage programming for water resources management under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 52(5), pages 800-812.
    4. Li, Y.P. & Huang, G.H. & Nie, S.L., 2009. "A robust interval-based minimax-regret analysis approach for the identification of optimal water-resources-allocation strategies under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 54(2), pages 86-96.
    5. Wang, S. & Huang, G.H., 2014. "An integrated approach for water resources decision making under interactive and compound uncertainties," Omega, Elsevier, vol. 44(C), pages 32-40.
    6. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    7. Changyu Zhou & Guohe Huang & Jiapei Chen, 2018. "A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China," Energies, MDPI, vol. 11(10), pages 1-21, October.
    8. Wang, S. & Huang, G.H., 2015. "A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management," European Journal of Operational Research, Elsevier, vol. 240(2), pages 572-581.
    9. Gaivoronski, Alexei & Sechi, Giovanni M. & Zuddas, Paola, 2012. "Cost/risk balanced management of scarce resources using stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 214-224.
    10. 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.
    11. Liu, Yuan & He, Li & Shen, Jing, 2017. "Optimization-based provincial hybrid renewable and non-renewable energy planning – A case study of Shanxi, China," Energy, Elsevier, vol. 128(C), pages 839-856.
    12. 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).
    13. Niu, G. & Li, Y.P. & Huang, G.H. & Liu, J. & Fan, Y.R., 2016. "Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 166(C), pages 53-69.
    14. Chenglong Zhang & Qiong Yue & Ping Guo, 2019. "A Nonlinear Inexact Two-Stage Management Model for Agricultural Water Allocation under Uncertainty Based on the Heihe River Water Diversion Plan," IJERPH, MDPI, vol. 16(11), pages 1-18, May.
    15. Li, Y.P. & Huang, G.H. & Wang, G.Q. & Huang, Y.F., 2009. "FSWM: A hybrid fuzzy-stochastic water-management model for agricultural sustainability under uncertainty," Agricultural Water Management, Elsevier, vol. 96(12), pages 1807-1818, December.
    16. Patoghi, Amirhosein & Mousavi, Seyed Meysam, 2021. "A new approach for material ordering and multi-mode resource constraint project scheduling problem in a multi-site context under interval-valued fuzzy uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Liu, Y. & Huang, G.H. & Cai, Y.P. & Cheng, G.H. & Niu, Y.T. & An, K., 2009. "Development of an inexact optimization model for coupled coal and power management in North China," Energy Policy, Elsevier, vol. 37(11), pages 4345-4363, November.
    18. Jian-Jun Wang & Zongli Dai & Ai-Chih Chang & Jim Junmin Shi, 2022. "Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations," Annals of Operations Research, Springer, vol. 315(1), pages 463-505, August.
    19. 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.
    20. Tubagus Robbi Megantara & Sudradjat Supian & Diah Chaerani, 2022. "Strategies to Reduce Ride-Hailing Fuel Consumption Caused by Pick-Up Trips: A Mathematical Model under Uncertainty," Sustainability, MDPI, vol. 14(17), pages 1-18, August.

    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:7:p:2015-2038. 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.