IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v24y2010i10p2221-2235.html
   My bibliography  Save this article

Chance Constrained Optimal Design of Composite Channels Using Meta-Heuristic Techniques

Author

Listed:
  • M. Janga Reddy
  • S. Adarsh

Abstract

Optimal design of irrigation channels has an important role in planning and management of irrigation projects. The input parameters used in design of irrigation channels are prone to uncertainty and may result in failure of channels. To improve the overall reliability and cost effectiveness, optimal design of composite channels is performed as a chance constrained problem in this study. The models are developed to minimize the total cost, while satisfying the specified probability of the channel capacity being greater than the design flow. The formulated model leads to a highly non-linear and non-convex optimization problem having multimodal behavior. In this paper, the usefulness of two meta-heuristic search algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are investigated to obtain the optimal solutions. Two site specific cases of restricted top width and restricted flow depth are also analyzed. It is found that both the algorithms performing quite well in giving optimal solutions and handling the additional constraints. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • M. Janga Reddy & S. Adarsh, 2010. "Chance Constrained Optimal Design of Composite Channels Using Meta-Heuristic Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 2221-2235, August.
  • Handle: RePEc:spr:waterr:v:24:y:2010:i:10:p:2221-2235
    DOI: 10.1007/s11269-009-9548-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-009-9548-5
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11269-009-9548-5?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. M. Reddy & D. Kumar, 2006. "Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 861-878, December.
    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. Yousef Hassanzadeh & Amin Abdi & Siamak Talatahari & Vijay Singh, 2011. "Meta-Heuristic Algorithms for Hydrologic Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(7), pages 1855-1879, May.
    2. Li, Xiaojuan & Kang, Shaozhong & Niu, Jun & Du, Taisheng & Tong, Ling & Li, Sien & Ding, Risheng, 2017. "Applying uncertain programming model to improve regional farming economic benefits and water productivity," Agricultural Water Management, Elsevier, vol. 179(C), pages 352-365.

    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. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.
    2. Wang Hua & Pang Yong, 2009. "Water Quantity Operation to Achieve Multi-Environmental Goals for a Waterfront Body," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(10), pages 1951-1968, August.
    3. Chao-Chung Yang & Liang-Cheng Chang & Chang-Shian Chen & Ming-Sheng Yeh, 2009. "Multi-objective Planning for Conjunctive Use of Surface and Subsurface Water Using Genetic Algorithm and Dynamics Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(3), pages 417-437, February.
    4. Yongqi Liu & Hui Qin & Li Mo & Yongqiang Wang & Duan Chen & Shusen Pang & Xingli Yin, 2019. "Hierarchical Flood Operation Rules Optimization Using Multi-Objective Cultured Evolutionary Algorithm Based on Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 337-354, January.
    5. Zhou, Jianzhong & Zhang, Yongchuan & Zhang, Rui & Ouyang, Shuo & Wang, Xuemin & Liao, Xiang, 2015. "Integrated optimization of hydroelectric energy in the upper and middle Yangtze River," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 481-512.
    6. J. Yazdi, 2018. "Improving Urban Drainage Systems Resiliency Against Unexpected Blockages: A Probabilistic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4561-4573, November.
    7. Haojianxiong Yu & Jianjian Shen & Chuntian Cheng & Jia Lu & Huaxiang Cai, 2023. "Multi-Objective Optimal Long-Term Operation of Cascade Hydropower for Multi-Market Portfolio and Energy Stored at End of Year," Energies, MDPI, vol. 16(2), pages 1-21, January.
    8. Hui Qin & Jianzhong Zhou & Youlin Lu & Yinghai Li & Yongchuan Zhang, 2010. "Multi-objective Cultured Differential Evolution for Generating Optimal Trade-offs in Reservoir Flood Control Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2611-2632, September.
    9. Tao Jiang & Ming Zhong & Ying-jie Cao & Long-jian Zou & Bo Lin & Ai-ping Zhu, 2016. "Simulation of Water Quality under Different Reservoir Regulation Scenarios in the Tidal River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3593-3607, August.
    10. J. Yazdi & M. Sabbaghian Moghaddam & B. Saghafian, 2018. "Optimal Design of Check Dams in Mountainous Watersheds for Flood Mitigation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4793-4811, November.
    11. Long Ho & Peter Goethals, 2020. "Research hotspots and current challenges of lakes and reservoirs: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 603-631, July.
    12. Aida Tayebiyan & Thamer Ahmed Mohammed Ali & Abdul Halim Ghazali & M. A. Malek, 2016. "Optimization of Exclusive Release Policies for Hydropower Reservoir Operation by Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1203-1216, February.
    13. Dan Yan & Saskia E. Werners & He Qing Huang & Fulco Ludwig, 2016. "Identifying and Assessing Robust Water Allocation Plans for Deltas Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5421-5435, November.
    14. Seyed-Mohammad Hosseini-Moghari & Reza Morovati & Mohammad Moghadas & Shahab Araghinejad, 2015. "Optimum Operation of Reservoir Using Two Evolutionary Algorithms: Imperialist Competitive Algorithm (ICA) and Cuckoo Optimization Algorithm (COA)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3749-3769, August.
    15. Behrang Beiranvand & Parisa-Sadat Ashofteh, 2023. "A Systematic Review of Optimization of Dams Reservoir Operation Using the Meta-heuristic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3457-3526, July.
    16. Andre Ferreira & Ramesh Teegavarapu, 2012. "Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(3), pages 707-732, February.
    17. Jiun-Huei Jang, 2023. "Optimizing the Cleaning Strategies to Reduce the Flood Risk Increased by Gully Blockages," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1747-1763, March.
    18. M. Alipour, 2015. "Risk-Informed Decision Making Framework for Operating a Multi-Purpose Hydropower Reservoir During Flooding and High Inflow Events, Case Study: Cheakamus River System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 801-815, February.
    19. J. Yazdi & A. Moridi, 2018. "Multi-Objective Differential Evolution for Design of Cascade Hydropower Reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4779-4791, November.
    20. J. Sreekanth & Bithin Datta & Pranab Mohapatra, 2012. "Optimal Short-term Reservoir Operation with Integrated Long-term Goals," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(10), pages 2833-2850, 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:24:y:2010:i:10:p:2221-2235. 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.