Water Resources Management

, Volume 22, Issue 10, pp 1367–1379 | Cite as

Application of Several Meta-Heuristic Techniques to the Optimization of Real Looped Water Distribution Networks

Article

Abstract

The optimization of looped water distribution systems is a complex problem as the pipe flows are unknown variables. Although many researchers have reported algorithms for minimizing the network cost applying a large variety of techniques, such as linear programming, non-linear programming, global optimization methods and meta-heuristic approaches, a totally satisfactory and efficient method is not available as yet. Many works have assessed the performance of these techniques using small or medium-sized benchmark networks proposed in the literature, but few of them have tested these methods with large-scale real networks. The aim of this paper is to evaluate the performance of several meta-heuristic techniques: genetic algorithms, simulated annealing, tabu search, and iterated local search. These techniques were first validated and compared by applying them to a medium-sized benchmark network previously reported in the literature. They were then applied to a large irrigation water distribution network that has been proposed in a previous work to assess their performance in a practical application. All the methods tested performed adequately well, compared with the results found in previous works. Genetic algorithm was more efficient when dealing with a medium-sized network, but other methods outperformed it when dealing with a real complex one.

Keywords

Water distribution system Pipe networks Optimization Heuristics 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abebe AJ, Solomatine DP (1998) Application of global optimization to the design of pipe networks. In: Proceedings of 3rd international conference of hydroinformatics, pp 989–996Google Scholar
  2. Alperovits E, Shamir U (1977) Design of optimal water distribution systems. Water Resour Res 13(6):885–900CrossRefGoogle Scholar
  3. Cunha MD, Sousa J (1999) Water distribution network design optimization: simulated annealing approach. Water Resour Planning Manag, ASCE 125(4):215–221CrossRefGoogle Scholar
  4. Eiger G, Shamir U, Ben-Tal A (1994) Optimal design of water distribution networks. Water Resour Res 30(9):2637–2646CrossRefGoogle Scholar
  5. Eusuff MM, Lansey KE (2003) Optimization of water distribution network design using the shuffled frog leaping algorithm. Water Resour Planning Manag, ASCE 129(3):210–225CrossRefGoogle Scholar
  6. Fujiwara O, Khang DB (1990) A two-phase decomposition method for optimal design of looped water distribution networks. Water Resour Res 26(4):539–549CrossRefGoogle Scholar
  7. Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness. Freeman, San FranciscoGoogle Scholar
  8. Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. Simulation 76(2):60–68CrossRefGoogle Scholar
  9. Gil C, Ortega J, Montoya MG, Baños R (2002) A mixed heuristic for circuit partitioning. Comput Optim Appl 23(3):321–340CrossRefGoogle Scholar
  10. Glover F, Laguna M, Dowsland KA (1993) Modern heuristic techniques for combinatorial problems. In: Reeves CR (ed). Blackwell, LondonGoogle Scholar
  11. Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison Wesley, New YorkGoogle Scholar
  12. Gupta I, Bassin JK, Gupta A, Khanna P (1993) Optimization of water distribution system. Environ Softw 8:101–113CrossRefGoogle Scholar
  13. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671CrossRefGoogle Scholar
  14. Lansey KE, Mays LW (1989) Optimal design of water distribution systems. Water Resour Planning Manag, ASCE 115(10):1401–1418Google Scholar
  15. Maier HR, Simpson AR, Zecchin AC, Foong WK, Phang KY, Seah HY, Tan CL (2003) Ant colony optimization for design of water distribution systems. Water Resour Planning Manag, ASCE 129(3):200–209CrossRefGoogle Scholar
  16. Metropolis N, Rosenbluth A, Rosenbluth M, Teller A, Teller E (1953) Equation of state calculations by fast computing machines. Chem Phys 21(6):1087–1092CrossRefGoogle Scholar
  17. Montesinos P, Garcia-Guzman A, Ayuso JL (1999) Water distribution network optimization using modified genetic algorithm. Water Resour Res 35(11):3467–3473CrossRefGoogle Scholar
  18. Quindry GE, Brill ED, Liebman JC (1981) Optimization of looped water distribution systems. J Environ Eng, ASCE 107(4):665–679Google Scholar
  19. Ramalhino H, Martin O, Stutzle T (2002) Iterated local search. In: Glover F, Kochenberger G (eds) Handbook of metaheuristics. Kluwer, Norwell, MA, pp 321–353Google Scholar
  20. Reca J, Martínez J (2006) Genetic algorithms for the design of looped irrigation water distribution networks. Water Resour Res 42(5):W05416, doi:10.1029/2005WR004383 CrossRefGoogle Scholar
  21. Rossman LA (2000) EPANET 2 user’s manual. EPA/600/R-00/057, 2000Google Scholar
  22. Savic DA, Walters GA (1997) Genetic algorithms for least-cost design of water distribution networks. Water Resour Planning Manag, ASCE 123(2):67–77CrossRefGoogle Scholar
  23. Sherali HD, Totlani R, Loganathan GV (1998) Enhanced lower bounds for the global optimization of water distribution networks. Water Resour Res 34(7):1831–1841CrossRefGoogle Scholar
  24. Talbi E (2002) A taxonomy of hybrid metaheuristics. J Heuristics 8(5):541–564CrossRefGoogle Scholar
  25. Todini E, Pilati S (1987) A gradient method for the analysis of pipe networks. In: Proceedings of international conference on computer applications for water supply and distribution. Leicester Polytechnic, UKGoogle Scholar
  26. Vairavamoorthy K, Ali M (2000) Optimal design of water distribution systems using genetic algorithms. Comput-Aided Civil Infrastruct Eng 15(5):374–382CrossRefGoogle Scholar
  27. Varma K, Narasimhan S, Bhallamudi SM (1997) Optimal design of water distribution systems using NLP method. J Environ Eng, ASCE 123(4):381–388CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.Department of Rural EngineeringUniversity of AlmeríaAlmeríaSpain
  2. 2.Department of Computer Architecture and ElectronicsUniversity of AlmeríaAlmeríaSpain

Personalised recommendations