Application of the NSGA-II multi-objective algorithm in the optimal design of drinking water distribution networks. Case: Huancavelica City, Peru
DOI:
https://doi.org/10.24850/j-tyca-2025-02-04Keywords:
NSGA-II, water distribution network, cost, hydraulic reliabilityAbstract
In recent times, several multi-objective genetic algorithms and their application in optimization of drinking water distribution networks have been developed, of which NSGA-II has shown the strongest performance. This research shows the application of NSGA-II in the optimal design of drinking water distribution networks considering cost (IC) and hydraulic reliability (IR) as objective functions. The research was carried out in response to a real problem related to water supply in the city of Huancavelica. Using the information obtained from EPS EMAPA Huancavelica S.A., and the Python programming language with the Epanet Toolkit, NSGA-II is validated by applying it to the design of the Hanoi network. Once validated, the Huancavelica network is analyzed, which has a IC of 0.31 equivalent to USD 140 099.89 and an IR of 0.25, and an optimal network design is obtained, which has a IC of 0.24 with a value of USD 117 590.12 and an IR of 0.23, which allows appreciating a difference in the IC of USD 22 509.77 and a reduction of the IR, which makes it a much more reliable network that simultaneously satisfies the minimum pressure restrictions in all the nodes, in addition to guaranteeing a capacity to withstand failure conditions during its operation. It is determined that NSGA-II is favorable for the optimal design of drinking water networks considering two objective functions of cost and hydraulic reliability.
References
Brkic, D., & Praks, P. (2018). Accurate and efficient explicit approximations of the colebrook flow friction equation based on the wright ω-function. Mathematics, 7(1). DOI: 10.3390/math7010034
Chu, X., & Yu, X. (2018). Improved crowding distance for NSGA-II. DOI: 10.48550/arxiv.1811.12667
Cunha, M. C., & Sousa, J. (1999). Water distribution network design optimization: Simulated annealing approach. Journal of Water Resources Planning and Management, 125(4). DOI: 10.1061/(ASCE)0733-9496(1999)125:4(215)
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2). DOI: 10.1109/4235.996017
EMAPA-HVCA, S. A. (2018). Plan maestro (2018-2047). Huancavelica, Perú: EPS EMAPA Huancavelica. Recuperado de https://www.emapahvca.com/muni.php/ver_documento/id/munihvca7b8c6de4d949b3e51c816a1d5173de5b.pdf/
Gunantara, N. (2018). A review of multi-objective optimization: Methods and its applications. Cogent Engineering, 5(1). DOI: 10.1080/23311916.2018.1502242
Liong, S. Y., & Atiquzzaman, M. (2004). Optimal design of water distribution network using shuffled complex evolution. Journal of The Institution of Engineers, Singapore, 44(1), 93-107.
Ostfeld, A. (2015). Water distribution networks. Studies in Computational Intelligence, 565. DOI: 10.1007/978-3-662-44160-2_4
Parvaze, S., Kumar, R., Khan, J. N., Al-Ansari, N., Parvaze, S., Vishwakarma, D. K., Elbeltagi, A., & Kuriqi, A. (2023). Optimization of water distribution systems using genetic algorithms: A review. Archives of Computational Methods in Engineering. DOI: 10.1007/s11831-023-09944-7
Peñuela, C. A., & Granada, M. (2007). Optimización multiobjetivo usando un algoritmo genético y un operador elitista basado en un ordenamiento no-dominado (NSGA-II). Scientia et Technica, 13(35), 175-180.
Prasad, T. D., & Park, N.-S. (2004). Multiobjective genetic algorithms for design of water distribution networks. Journal of Water Resources Planning and Management, 130(1). DOI: 10.1061/(asce)0733-9496(2004)130:1(73)
Rahimi, I., Gandomi, A. H., Deb, K., Chen, F., & Nikoo, M. R. (2022). Scheduling by NSGA-II: Review and bibliometric analysis. Processes, 10. DOI: 10.3390/pr10010098
Renata, R. T., Pereira, F. F. S., Da Silva, T. B. G., Castro, E. R., & Saad, J. C. C. (2020). The performance of explicit formulas for determining the darcyweisbach friction factor. Engenharia Agricola, 40(2). DOI: 10.1590/1809-4430-ENG.AGRIC.V40N2P258-265/2020
RNE, Reglamento Nacional de Edificaciones. (2009). Redes de distribución de agua para consumo humano (OS.050). Lima, Perú: Reglamento Nacional de Edificaciones. Recuperado de https://ww3.vivienda.gob.pe/ejes/vivienda-y-urbanismo/documentos/Reglamento%20Nacional%20de%20Edificaciones.pdf
Rossman, L. A. (September, 2000). EPANET 2 Users Manual EPA/600/R-00/57. Washington, DC, USA: Water Supply and Water Resources Division, U.S. Agency, Environmental Protection.
Saldarriaga, J., Páez, D., Salcedo, C., Cuero, P., López, L. L., León, N., & Celeita, D. (2020). A direct approach for the near-optimal design of water distribution networks based on power use. Water, 12(4). DOI: 10.3390/W12041037
Saldarriaga, J., Salcedo, C., González, M. A., Ortiz, C., Wiesner, F., & Gómez, S. (2022). On the evolution of the optimal design of WDS: Shifting towards the use of a fractal criterion. Water, 14(23), 3795. DOI: 10.3390/W14233795/S1
Saldarriaga, J. (2007). Hidráulica de tuberías : abastecimiento de agua, redes, riegos. Bogotá, Colombia: Alfaomega.
Sangroula, U., Han, K. H., Koo, K. M., Gnawali, K., & Yum, K. T. (2022). Optimization of water distribution networks using genetic algorithm based SOP-WDN Program. Water, 14(6). DOI: 10.3390/w14060851
Savic, D. A., & Walters, G. A. (1997). Genetic algorithms for leastcost design of water distribution networks. Journal of Water Resources Planning and Management, 123(2). DOI: 10.1061/(ASCE)0733-9496(1997)123:2(67)
Suribabu, C. R., & Neelakantan, T. R. (2014). Optimal upgradation and expansion of existing water distribution networks using differential evolution algorithm. Asian Journal of Applied Sciences, 7(6). DOI: 10.3923/ajaps.2014.375.390
Swamee, P. K., & Jain, A. K. (1976). Explicit equations for pipe-flow problems. ASCE Journal of the Hydraulics Division, 102(5). DOI: 10.1061/jyceaj.0004542
Todini, E. (2000). Looped water distribution networks design using a resilience index based heuristic approach. Urban Water, 2(2). DOI: 10.1016/s1462-0758(00)00049-2
Wang, Q., Guidolin, M., Savic, D., & Kapelan, Z. (2015). Two-objective design of benchmark problems of a water distribution system via MOEAs: Towards the best-known approximation of the true Pareto front. Journal of Water Resources Planning and Management, 141(3). DOI: 10.1061/(asce)wr.1943-5452.0000460
Wang, Q., Wang, L., Huang, W., Wang, Z., Liu, S., & Savić, D. A. (2019). Parameterization of NSGA-II for the optimal design of water distribution systems. Water, 11(5). DOI: 10.3390/w11050971
Wright, R., Parpas, P., & Stoianov, I. (2015). Experimental investigation of resilience and pressure management in water distribution networks. Procedia Engineering, 119(1). DOI: 10.1016/j.proeng.2015.08.917
Yazdandoost, F., & Izadi, A. (2016). A decision-making framework for designing water distribution networks based on multi-objective optimisation. International Journal of Multicriteria Decision Making, 6(4). DOI: 10.1504/IJMCDM.2016.081379
Zarei, N., Azari, A., & Heidari, M. M. (2022). Improvement of the performance of NSGA-II and MOPSO algorithms in multi-objective optimization of urban water distribution networks based on modification of decision space. Applied Water Science, 12(6), 1-12. DOI: 10.1007/S13201-022-01610-W/TABLES/5
Zheng, F., Zecchin, A. C., Maier, H. R., & Simpson, A. R. (2016). Comparison of the Searching Behavior of NSGA-II, SAMODE, and Borg MOEAs applied to water distribution system design problems. Journal of Water Resources Planning and Management, 142(7). DOI: 10.1061/(asce)wr.1943-5452.0000650
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