Abstract
The electrical energy cost represents a significant fraction of the total cost in a water supply system. Any optimization in pumping operational procedures results in a reduction of this cost. The aim of this paper is the optimization of pump operation in a water distribution system, located at Guarapuava, Brazil. For this, we used two techniques of Natural Computing: Genetic Algorithms and Shuffled Frog Leaping Algorithm. Both techniques were effective when comparing with a traditional approach. However, in our experiments, the SFLA achieved lower costs.
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De Paula Castanho, M. J., de Ré, A. M., Hernandes, F., da Costa Luz, E., Miazaki, M., & Rautenberg, S. (2016). Natural computing in pump-scheduling optimization for water supply system: Case study. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9692, pp. 359–369). Springer Verlag. https://doi.org/10.1007/978-3-319-39378-0_31
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