Advertisement

OPTIMAL MODEL ON CANAL WATER DISTRIBUTION BASED ON DYNAMIC PENALTY FUNCTION AND GENETIC ALGORITHM

  • Wenju Zhao
  • Xiaoyi Ma
  • Yinhong Kang
  • Hongyi Ren
  • Baofeng Su
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 294)

Abstract

The present optimal water delivery scheduling models are based on the assumed equal design discharges of lateral canals, which are not in accordance with practical water delivery scheduling demand in most irrigation systems. In order to solve this problem, a model of lateral canals with unequal discharges and a solution method were proposed; At present, traditional fixed penalty factor have some problem, such as it is difficulty to use unified dimension and to get a higher searching precision, besides, it prematurely converge to local optimal solution. Therefore, the thought of simulated annealing was referred to design a dynamic penalty function. In the progress of genetic operation, the SGA (Simple Genetic Algorithm) adopted adaptive crossover mutation method, and compared distinct solutions of model which based on the method in this paper, Adaptive genetic algorithm (AGA) and traditional methods used in irrigation district widely respectively. Comparing with water delivery plan compiled using traditional methods, the results illustrate that using this method can get much more reasonable lateral canals water delivery time and homogeneous discharges of upper canal. AGA can adjust the genetic controlling parameters automatically on the basis of values of individual fitness and degree of population dispersion, and get a high precision solution. So it has a higher practical value in irrigation system management.

Keywords

Penalty Function Water Distribution Water Delivery Irrigation District Penalty Function Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Anwar, A.A., Clarke, D. Irrigation scheduling using mixed-integer linear programming. J. Irrigat. Drain.Eng., 2001, 127 (2), 63–69.CrossRefGoogle Scholar
  2. Kang, S.Z., Cai, H.J., Agricultural Water Management Science. China Agriculture Press, Beijing, 1996. (in Chinese).Google Scholar
  3. Lv, H.X., Xiong, Y.Z., Wang, Z.N. Optimal Model of Rotation Irrigation Distribution Channel and Branch Canal and Delivery Time. Trans. CSAE.,2000, 16(6),43–46. (in Chinese).Google Scholar
  4. Reddy, J.M., Wilamowski, B., Cassel-Sharmasarkar, F. Optimal scheduling of irrigation for lateral canals. ICID J., 1999,48 (3), 1–12.Google Scholar
  5. Song, S.B., Lv, H.X. Optimization Model of Rotation Irrigation Channel Distribution and Solution with Genetic Algorithm. Trans. CSAE., 2004, 20(2):40 – 44. (in Chinese).Google Scholar
  6. Srinivas, M., Patnaik, L.M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms. IEEE Transon Systems Man and Cybernetics., 1994, 24(4), 656 – 667.CrossRefGoogle Scholar
  7. Suryavanshi, A.R., Reddy, J.M. Optimal operation schedule of irrigation distribution systems. Agric. Water Manage, 1986, 11(1), 23–30.CrossRefGoogle Scholar
  8. Wang, X.P., Cai, L.M. Genetic Algorithm-Theory, Application and Software Realization. Xi'an Jiaotong University Press. Xi'an, 2002. (in Chinese).Google Scholar
  9. Wang, Z., Reddy, J.M., Feyen, J. Improved 0–1 programming model for optimal flow scheduling in irrigation canals. Irrigat. Drain. Syst, 1995, 14(9), 105–116.CrossRefGoogle Scholar
  10. Wang, Z.N. Irrigation and Drainage Engineering. China Agriculture Press. Beijing, 2000. (in Chinese).Google Scholar
  11. Wardlaw R., Bhaktikul K. Comparison of Genetic Algorithm and Linear Programming Approaches for Lateral Canal Scheduling. J. Irrig. and Drain. Engrg., 2004, 130(4), 311–317.CrossRefGoogle Scholar
  12. Wu, Z.Y., Shao, H.H, Wu, X.Y. Annealing Accuracy Penalty Function Based Nonlinear Constrained Optimization Method with Genetic Algorithms. Control and Decision., 1998, 13(2): 136–140. (in Chinese).MathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Wenju Zhao
    • 1
  • Xiaoyi Ma
    • 1
  • Yinhong Kang
    • 1
  • Hongyi Ren
    • 1
  • Baofeng Su
    • 1
  1. 1.Northwest Agriculture and Forest UniversityYanglingChina

Personalised recommendations