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A Memetic Algorithm for Water Distribution Network Design

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Soft Computing in Industrial Applications

Part of the book series: Advances in Soft Computing ((AINSC,volume 39))

Abstract

The majority of real optimization problems cannot be solved exactly because they have very large and highly complex search spaces. One of these complex problems is the design of looped water distribution networks, which consists of determining the best way of conveying water from the sources to the users, satisfying their requirements. This paper is to present a new memetic algorithm and evaluate its performance in this problem. With the aim to establish an accurate conclusion, other four heuristic approaches have also been adapted, including simulated annealing, mixed simulated annealing and tabu search, iterated local search, and scatter search. Results obtained in two water distribution networks demonstrate that the memetic algorithm works better when the size of the problem increases.

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References

  1. Moscato, P.: Memetic Algorithms: A Short Introduction. In: Glover, F., et al. (eds.) New Ideas in Optimization, pp. 219–234. McGraw-Hill, New York (1999)

    Google Scholar 

  2. Holland, J.: Adaptation in Natural and Artificial Systems. MIT Press, Cambridge (1975)

    Google Scholar 

  3. Dawkins, R.: The Selfish Gene. Oxford University Press, New York (1976)

    Google Scholar 

  4. Krasnogor, N., Gustafson, S.: Toward Truly ”Memetic” Memetic Algorithms: Discussion and Proof of Concepts. In: Corne, D., et al. (eds.) Advances in Nature-Inspired Computation: The PPSN VII Workshops (2002)

    Google Scholar 

  5. Gupta, I., et al.: Optimization of Water Distribution System. Environmental Software 8, 101–113 (1993)

    Article  Google Scholar 

  6. Alperovits, E., Shamir, U.: Design of Optimal Water Distribution Systems. Water Resources Research 13(6), 885 (1977)

    Google Scholar 

  7. Fujiwara, O., Khang, D.B.: A Two-phase Decomposition Method for Optimal Design of Looped Water Distribution Networks. Water Resources Research 26(4), 539–549 (1990)

    Article  Google Scholar 

  8. Varma, K.V.K., Narasimhan, S., Bhallamudi, S.M.: Optimal Design of Water Distribution Systems Using NLP Method. Journal of Environmental Engineering, ASCE 381, 381 (1997)

    Article  Google Scholar 

  9. Sherali, H.D., Totlani, R., Loganathan, G.V.: Enhanced Lower Bounds for the Global Optimization of Water Distribution Networks. Water Resources Research 34(7), 1831–1841 (1998)

    Article  Google Scholar 

  10. Cunha, M.D., Sousa, J.: Water Distribution Network Design Optimization: Simulated Annealing Approach. Journal Of Water Resources Planning And Management, ASCE 125(4), 215 (1999)

    Article  Google Scholar 

  11. Vairavamoorthy, K., Ali, M.: Optimal Design of Water Distribution Systems using Genetic Algorithms. Computer-Aided Civil and Infraestructure Engineering 15, 372–382 (2000)

    Google Scholar 

  12. Maier, H.R., et al.: Ant Colony Optimization for Design of Water Distribution Systems. J. of Water Resources Planning and Management, ASCE 129(3), 200–209 (2003)

    Article  Google Scholar 

  13. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by Simulated Annealing. Science 220, 671 (1983)

    Article  MathSciNet  Google Scholar 

  14. Gil, C., et al.: A Mixed Heuristic for Circuit Partitioning. Computational Optimization and Applications Journal 23(3), 321–340 (2002)

    Article  MATH  Google Scholar 

  15. Ramalhino, H., Martin, O., Stutzle, T.: Iterated Local Search. In: Glover, F., et al. (eds.) Handbook of Metaheuristics, pp. 321–353. Kluwer, Norwell (2002)

    Google Scholar 

  16. Marti, R., Glover, F.: Principles of Scatter Search. European Journal of Operations Research 169(2), 359–372 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  17. Talbi, E.: A Taxonomy of Hybrid Metaheuristics. Journal of Heuristics 8(5), 541–564 (2002)

    Article  Google Scholar 

  18. Davidor, Y., Ben-Kiki, O.: The Interplay Among the Genetic Algorithm Operators: Information Theory Tools Used in a Holistic Way. In: Manner, R., et al. (eds.) Parallel Problem Solving from Nature (PPSN II), pp. 77–86 (2002)

    Google Scholar 

  19. Savic, D.A., Walters, G.A.: Genetic Algorithms for Least-Cost Design of Water Distribution Networks. Journal of Water Resources Planning and Management, ASCE 123(2), 67–77 (1997)

    Article  Google Scholar 

  20. Montesinos, P., Garcia-Guzman, A., Ayuso, J.L.: Water Distribution Network Optimisation using Modified Genetic Algorithm. Water Resources Research 35(11), 3467–3473 (1999)

    Article  Google Scholar 

  21. Watters, G.Z., Keller, J.: Trickle Irrigation Tubing Hydraulics, ASAE Paper No. 78-2015, p.18. ASAE, St. Joseph, Michigan (1978)

    Google Scholar 

  22. Rossman, L.A.: EPANET 2 user’s manual, EPA/600/R-00/057 (September 2000)

    Google Scholar 

  23. Todini, E., Pilati, S.: A Gradient Method for the Analysis of Pipe Networks. In: Int. Conf. on Computer Applications for Water Supply and Distribution, UK (1987)

    Google Scholar 

  24. Cotta, C.: Scatter Search and Memetic Approaches to the Error Correcting Code Problem. In: Gottlieb, J., Raidl, G.R. (eds.) EvoCOP 2004. LNCS, vol. 3004, pp. 51–61. Springer, Heidelberg (2004)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Departamento de Arquitectura de Computadores y Electrónica, Universidad de Almería, La Cañada de San Urbano s/n, 04120 Almería, Spain

    R. Baños, C. Gil & J. I. Agulleiro

  2. Departamento de Ingeniería Rural, Universidad de Almería, La Cañada de San Urbano s/n, 04120 Almería, Spain

    J. Reca

Authors
  1. R. Baños
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  2. C. Gil
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  3. J. I. Agulleiro
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  4. J. Reca
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Editor information

Ashraf Saad Keshav Dahal Muhammad Sarfraz Rajkumar Roy

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© 2007 Springer-Verlag Berlin Heidelberg

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Baños, R., Gil, C., Agulleiro, J.I., Reca, J. (2007). A Memetic Algorithm for Water Distribution Network Design. In: Saad, A., Dahal, K., Sarfraz, M., Roy, R. (eds) Soft Computing in Industrial Applications. Advances in Soft Computing, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70706-6_26

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  • DOI: https://doi.org/10.1007/978-3-540-70706-6_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70704-2

  • Online ISBN: 978-3-540-70706-6

  • eBook Packages: EngineeringEngineering (R0)

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