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Ant Colony Optimization for the Design of Small-Scale Irrigation Systems

Author

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  • Qin Tu
  • Hong Li
  • Xinkun Wang
  • Chao Chen

Abstract

The optimal design of sprinkler irrigation systems is a complicated nonlinear programming problem that is related to the performance of the system and meanwhile an economic problem to farmers in developing countries. Ant colony optimization (ACO), a meta-heuristic algorithm with the strategies inspired by foraging ants, was considered. Exactly an Ant Cycle System was proposed to solve this problem. The performance of ACO was compared to that of Genetic Algorithm (GA), and the optimal results were further validated by field tests on four small-scale irrigation systems. In the optimization model, the objective function was minimizing the specific energy consumption subject to the constraints of pipe diameters, number of sprinklers and working pressure of the end sprinkler along the pipeline and pump-pipeline cooperation conditions. In the design of ACO, head loss between adjacent sprinklers was introduced in the heuristic function to represent the distance between two cities in a Travelling Salesman Problem (TSP). And the fitness composed of the specific energy consumption dealt with penalty function was taken instead of the total length of a route in the pheromone updating. The results indicate that the specific energy consumption has been decreased in average by 12.45 % through ACO, 10.27 % through GA and 11.27 % from field tests compared to that in the initial configurations with irrigation uniformities higher than 75 % in the field tests. ACO implementation outperforms genetic algorithm in efficiency and reliability especially in larger systems. The ACO may provide a promising approach for the optimization of irrigation systems. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Qin Tu & Hong Li & Xinkun Wang & Chao Chen, 2015. "Ant Colony Optimization for the Design of Small-Scale Irrigation Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2323-2339, May.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:7:p:2323-2339
    DOI: 10.1007/s11269-015-0943-9
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    References listed on IDEAS

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    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. D. Kumar & M. Reddy, 2006. "Ant Colony Optimization for Multi-Purpose Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 879-898, December.
    3. Qin Tu & Hong Li & Xinkun Wang & Chao Chen & Yin Luo & Frank Dwomoh, 2014. "Multi-Criteria Evaluation of Small-Scale Sprinkler Irrigation Systems Using Grey Relational Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4665-4684, October.
    4. Md. Hossain & A. El-shafie, 2013. "Intelligent Systems in Optimizing Reservoir Operation Policy: A Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3387-3407, July.
    5. Ajay Singh, 2014. "Irrigation Planning and Management Through Optimization Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 1-14, January.
    6. F. Carrión & J. Montero & J. Tarjuelo & M. Moreno, 2014. "Design of Sprinkler Irrigation Subunit of Minimum Cost with Proper Operation. Application at Corn Crop in Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(14), pages 5073-5089, November.
    7. K. Srinivasa Raju & D. Nagesh Kumar, 2004. "Irrigation Planning using Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(2), pages 163-176, April.
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    Cited by:

    1. Penghui Ma & Yajin Hu & Hansheng Liu, 2019. "Optimal Design for Pressurized Irrigation Subunits with a Minimum Cost and Maximum Area for Uniformly Sloping Fields," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2711-2726, June.
    2. Penghui Ma & Yajin Hu & Hansheng Liu & Yuannong Li, 2020. "The Optimum Design Criteria for On-demand Pressurized Microirrigation Network Systems: Optimizing Subunits with Paired Laterals based on the Maximum Size," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3237-3255, August.

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