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Application of Differential Evolution for Irrigation Planning: An Indian Case Study

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  • A. Vasan
  • Komaragiri Raju

Abstract

The present paper demonstrates the applicability of population based search optimization method, namely, Differential Evolution (DE) to a case study of Mahi Bajaj Sagar Project (MBSP), India. Ten different strategies of DE are employed to assess the ability of DE for solving higher dimensional problems as an alternative methodology for irrigation planning. The parameters considered in DE are population size, crossover constant and weighting factor. Linear Programming (LP) is utilized as a comparative approach to assess the ability of DE. Comparison of results of LP and the 10 DE strategies for the given parameters indicated that both the results are comparable even for high dimensional problems. Extensive sensitivity analysis studies, performed for 3,600 combinations of above parameters for the 10 DE strategies suggested that DE/rand-to-best/1/bin strategy is the best strategy giving maximum benefits taking minimum CPU time. It is concluded that DE can be utilized for efficient planning of any irrigation system with suitable modifications. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • A. Vasan & Komaragiri Raju, 2007. "Application of Differential Evolution for Irrigation Planning: An Indian Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(8), pages 1393-1407, August.
    • Handle: RePEc:spr:waterr:v:21:y:2007:i:8:p:1393-1407
    DOI: 10.1007/s11269-006-9090-7
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    Cited by:

    1. Jun Guo & Jianzhong Zhou & Qiang Zou & Yi Liu & Lixiang Song, 2013. "A Novel Multi-Objective Shuffled Complex Differential Evolution Algorithm with Application to Hydrological Model Parameter Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2923-2946, June.
    2. R. Arunkumar & V. Jothiprakash, 2013. "Chaotic Evolutionary Algorithms for Multi-Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5207-5222, December.
    3. Jiang Wu & Jianzhong Zhou & Lu Chen & Lei Ye, 2015. "Coupling Forecast Methods of Multiple Rainfall–Runoff Models for Improving the Precision of Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5091-5108, November.
    4. Mehrdad Taghian & Iman Ahmadianfar, 2018. "Maximizing the Firm Energy Yield Preserving Total Energy Generation Via an Optimal Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 141-154, January.
    5. Xiangtao Li & Huawen Liu & Minghao Yin, 2013. "Differential Evolution for Prediction of Longitudinal Dispersion Coefficients in Natural Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5245-5260, December.
    6. Iman Ahmadianfar & Arvin Samadi-Koucheksaraee & Omid Bozorg-Haddad, 2017. "Extracting Optimal Policies of Hydropower Multi-Reservoir Systems Utilizing Enhanced Differential Evolution Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4375-4397, November.
    7. Mansouri, R., 2018. "Economical Optimization of the Pressure Irrigation Networks by using Developed Central Force Optimization Algorithm," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275982, International Association of Agricultural Economists.
    8. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.
    9. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.

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