Discussion of “Boosting Genetic Algorithm Performance in Pump Scheduling Problems with a Novel Decision-Variable Representation” by Luigi Cimorelli, Andrea D’Aniello, and Luca Cozzolino
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VIEW THE ORIGINAL ARTICLEAuthors: Luis Henrique Magalhães Costa https://orcid.org/0000-0002-1781-4188 [email protected] and Bruno de Athayde Prata https://orcid.org/0000-0002-3920-089X [email protected]Author Affiliations
Publication: Journal of Water Resources Planning and Management
Volume 147, Issue 9
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Data Availability Statement
We are sharing the source code of the B&B algorithm presented by Costa et al. (2016), assuming the depth-first-search criterion, for the Case Study 1—Any Town Modified, as reported by the authors. The code was developed in C#.net language, and it can be compiled by Visual Studio 2019 IDE. The project is available in the following link: https://github.com/luishenrique-uva/branch-bound-epanet.
Acknowledgments
The support of the National Council for Scientific and Technological Development (CNPq) and Coordination for the Improvement of Higher Education Personnel (CAPES) are acknowledged and appreciated.
References
Bäck, T., D. B. Fogel, and Z. Michalewicz. 2000. Evolutionary computation 1: Basic algorithms and operators. London: CRC Press.
Costa, L. H. M., B. de Athayde Prata, H. M. Ramos, and M. A. H. de Castro. 2016. “A branch-and-bound algorithm for optimal pump scheduling in water distribution networks.” Water Resour. Manage. 30 (3): 1037–1052. https://doi.org/10.1007/s11269-015-1209-2.
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© 2021 American Society of Civil Engineers.
History
Received: Apr 1, 2020
Accepted: Jul 9, 2020
Published online: Jun 17, 2021
Published in print: Sep 1, 2021
Discussion open until: Nov 17, 2021
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Authors
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Professor, Dept. of Civil Engineering, Vale do Acaraú State Univ., Sobral, Ceará 62040-370, Brazil. ORCID: https://orcid.org/0000-0002-1781-4188. Email: [email protected]
Professor, Dept. of Industrial Engineering, Federal Univ. of Ceará, Fortaleza, Ceará 60455-900, Brazil (corresponding author). ORCID: https://orcid.org/0000-0002-3920-089X. Email: [email protected]
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