Abstract
A water distribution network consists of many nodes interconnected to provide water to consumers. The importance and huge capital cost of the system lead to their design optimization. The present work proposes an intelligent optimization solver based on a Hybrid Simulated Annealing (HSA) to solve this problem. One of the main HSA control parameters is the Markov Chain Length (MCL), which is the number of moves to reach the equilibrium state at each temperature value. Our main objective is to analyze the HSA behavior by considering static and dynamic methods to compute the MCL. We test the HSA approaches using networks reported in the state-of-the-art and a real and new median size network that arises from a regional requirement. The experimentation suggests the use of a dynamic method, which exhibits the balance between solution quality and computational effort.
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Notes
- 1.
CORPICO is the Regional Cooperative for Electricity, Works and other Services in the city of General Pico, province of La Pampa, Argentina.
- 2.
The base loads can be found in the EPANET input files of the instances.
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Acknowledgments
The authors acknowledge the support of Universidad Nacional de La Pampa (Project FI-CD-151/15 and POIRe-03-2019) and the Incentive Program from MINCyT. The last author is also funded by CONICET.
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Bermudez, C., Alfonso, H., Minetti, G., Salto, C. (2021). Hybrid Simulated Annealing to Optimize the Water Distribution Network Design: A Real Case. In: Pesado, P., Eterovic, J. (eds) Computer Science – CACIC 2020. CACIC 2020. Communications in Computer and Information Science, vol 1409. Springer, Cham. https://doi.org/10.1007/978-3-030-75836-3_2
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