Advertisement

Heuristics and Simulation for Water Tank Optimization

  • Corinna Hallmann
  • Sascha Burmeister
  • Michaela Wissing
  • Leena Suhl
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 889)

Abstract

In the last two decades, water consumption in Germany has been decreasing which causes water tanks and pipes in water distribution systems to work inefficiently. This paper presents a mathematical optimization model to optimize water tanks in a water distribution system. Due to the hydraulic properties in water distribution systems the model is a non-convex Mixed Integer Quadratically Constrained Program (MIQCP). For problem instances of realistic size, the model cannot be solved within reasonable time with exact solution methods. We use different heuristic solution methods to solve the problem, such as a Simulated Annealing (SA) algorithm, a Shuffled Complex Evolution (SCE) algorithm as well as a Shuffled Frog-Leaping Algorithm (SFLA). These methods are combined with a hydraulic simulation to evaluate the solutions. The results of each method are compared to an exact solution method and discussed in this paper.

References

  1. 1.
    Ansótegui, C., Sellmann, M., Tierney, K.: A gender-based genetic algorithm for the automatic configuration of algorithms. In: Gent, I.P. (ed.) CP 2009. LNCS, vol. 5732, pp. 142–157. Springer, Heidelberg (2009).  https://doi.org/10.1007/978-3-642-04244-7_14CrossRefGoogle Scholar
  2. 2.
    Barakat, S.A., Altoubat, S.: Application of evolutionary global optimization techniques in the design of RC water tanks. Eng. Struct. 31(2), 332–344 (2009)CrossRefGoogle Scholar
  3. 3.
    Berthold, T., Heinz, S., Vigerske, S.: Extending a CIP framework to solve MIQCPs. In: Lee, J., Leyffer, S. (eds.) Mixed Integer Nonlinear Programming. Springer, New York (2012).  https://doi.org/10.1007/978-1-4614-1927-3_15CrossRefGoogle Scholar
  4. 4.
    Boulos, P.F., Lansey, K.E., Karney, B.W.: Comprehensive Water Distribution Systems Analysis Handbook for Engineers and Planners. MWH Soft, Pasadena (2006)Google Scholar
  5. 5.
    Bragalli, C., D’Ambrosio, C., Lee, J., Lodi, A., Toth, P.: On the optimal design of water distribution networks: a practical MINLP approach. Optim. Eng. 13(2), 219–246 (2012)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Duan, Q., Sorooshian, S., Gupta, V.: Shuffled complex evolution approach for effective and efficient global minimization. J. Optim. Theor. Appl. 76(3), 501–521 (1993)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Eusuff, M., Lansey, K., Pasha, F.: Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Eng. Opt. 38(2), 129–154 (2006)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Farmani, R., Walters, G.A., Savic, D.A.: Trade-off between total cost and reliability for Anytown water distribution network. J. Water Resour. Plan. Manag. 131(3), 161–171 (2005)CrossRefGoogle Scholar
  9. 9.
    Hallmann, C., Suhl, L.: Optimizing water tanks in water distribution systems by combining network reduction, mathematical optimization and hydraulic simulation. OR Spectr. 38(3), 577–595 (2016)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Karger, R., Cord-Landwehr, K., Hoffmann, F.: Wasserversorgung. Vieweg Verlag, Wiesbaden (2008)Google Scholar
  11. 11.
    Kurek, W., Ostfeld, A.: Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems. J. Environ. Manag. 115, 189–197 (2013)CrossRefGoogle Scholar
  12. 12.
    Nickel, D., Lange, M.A., Ayres, A., Schielein, J., Oelmann, M.: Ökologische und hygienische Kennzahlen im Benchmarking der Wasserversorgung: Empfehlungen aus Sicht des Gewässer- und Gesundheitsschutzes. Text 16/2013 des Umweltbundesamtes (2013)Google Scholar
  13. 13.
    Rautenberg, J., Fritsch, P., Hoch, W., Merkl, G., Otillinger, F., Weiß, M., Wricke, B.: Mutschmann/Stimmelmayr Taschenbuch der Wasserversorgung. Vieweg Verlag, Wiesbaden (2014)CrossRefGoogle Scholar
  14. 14.
    Rossman, L.A.: EPANET 2 - Users Manual. Water Supply and Water Resources Division, National Risk Management Research Laboratory, Cincinnati (2000)Google Scholar
  15. 15.
    Vamvakeridou-Lyroudia, L.: Tank simulation for the optimization of water distribution networks. J. Hydraul. Eng. 133(6), 625–636 (2007)CrossRefGoogle Scholar
  16. 16.
    Zheng, F., Zecchin, A., Newman, J., Maier, H., Dandy, G.: An adaptive convergence-trajectory controlled ant colony optimization algorithm with application to water distribution system design problems. IEEE Trans. Evol. Comput. 21, 773–791 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Decision Support and Operations Research LabPaderborn UniversityPaderbornGermany

Personalised recommendations