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Multiobjective genetic algorithms for pump scheduling in water supply

  • Progress in Evolutionary Scheduling
  • Conference paper
  • First Online:
Evolutionary Computing (AISB EC 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1305))

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Abstract

Cost minimisation is the main issue for water companies when establishing pumping regimes for water distribution. Energy consumption and pump maintenance represent by far the biggest expenditure, accounting for around 90% of the lifetime cost of a water pump. This paper introduces multiobjective Genetic Algorithms (GAs) for pump scheduling in water supply systems. The two objectives considered are minimisation of energy and maintenance costs. Pump switching is introduced as a surrogate measure of maintenance cost. The multiobjective algorithm is compared to the single objective GA, with both techniques improved by using hybridisation with a local-search method.

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References

  1. Goldberg, D.E., 1989, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley.

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  2. Hicks, et al., 1971, Pump Applications Engineering, McGraw-Hill, New York.

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  3. Lansey, K.E. and K. Awumah, 1994, Optimal Pump Operations Considering Pump Switches, Journal of Water Resources Planning and Management, ASCE, 120(1), 17–35.

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  4. Mäckle, G., D.A. Savic and G.A. Walters, (1995), Application of Genetic Algorithms to Pump Scheduling for Water Supply, Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA `95, IEE Conference Publication No. 414, Sheffield, UK, pp. 400–405.

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Author information

Authors and Affiliations

  1. School of Engineering, University of Exeter, EX4 4QF, Exeter, UK

    Dragan A. Savic & Godfrey A. Walters

  2. ERASMUS student, University of Stuttgart, Stuttgart, Germany

    Martin Schwab

Authors
  1. Dragan A. Savic
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  2. Godfrey A. Walters
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  3. Martin Schwab
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Editor information

David Corne Jonathan L. Shapiro

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© 1997 Springer-Verlag Berlin Heidelberg

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Savic, D.A., Walters, G.A., Schwab, M. (1997). Multiobjective genetic algorithms for pump scheduling in water supply. In: Corne, D., Shapiro, J.L. (eds) Evolutionary Computing. AISB EC 1997. Lecture Notes in Computer Science, vol 1305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027177

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  • DOI: https://doi.org/10.1007/BFb0027177

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63476-8

  • Online ISBN: 978-3-540-69578-3

  • eBook Packages: Springer Book Archive

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