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: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9692. Springer, Cham. https://doi.org/10.1007/978-3-319-39378-0_31
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DOI: https://doi.org/10.1007/978-3-319-39378-0_31
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