Preconditioning Water Distribution Network Optimization with Head Loss–Based Design Method
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 12
Abstract
This paper develops a new domain knowledge–based initial design method for the optimization of water distribution network design. The new initial water distribution network design method, termed as head loss-based design preconditioner (HDP), is based on head loss analysis in the supplying path from source to user. The new HDP-preconditioned search is compared with two algorithms: one preconditioned on a velocity-based initial design method and a simple genetic algorithm without preconditioning. Results show the HDP head loss–based method outperforms the prescreened heuristic sampling method (PHSM) in terms of the quality of the initial solutions and computational efficiency on all three cases. HDP also outperforms stochastic initialization on two of the three cases. The results obtained imply that the proposed domain knowledge–based design method HDP also would be able to provide effective starting conditions for other optimization algorithms, besides genetic algorithm for large water distribution systems, since most optimization methods are greatly assisted by a good starting condition.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, and code that support the findings of this study are available from the first or corresponding author upon reasonable request.
Acknowledgments
This work was initiated when Dr. Liu Haixing visited the Civil and Environmental Engineering Department, National University of Singapore (NUS), with Professor Shoemaker for 1 year. This study was funded by the National Natural Science Foundation of China (91647201, 91747102, 51579027, 51708086). This study was also supported by the Liaoning Natural Science Foundation (2019-MS-043) and the Fundamental Research Funds for the Central Universities [DUT18RC(3)072]. Professor Shoemaker’s start-up grant from NUS provided partial support. We would like to thank the editors and the anonymous reviewers for their insightful comments that have helped improve the quality of the paper.
References
Andrade, M., D. Kang, C. Choi, and K. Lansey. 2012. “Heuristic postoptimization approaches for design of water distribution systems.” J. Water Resour. Plann. Manage. 139 (4): 387–395. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000265.
Bi, W., G. C. Dandy, and H. R. Maier. 2015. “Improved genetic algorithm optimization of water distribution system design by incorporating domain knowledge.” Environ. Modell. Software 69 (Jul): 370–381. https://doi.org/10.1016/j.envsoft.2014.09.010.
Bragalli, C., C. D’Ambrosio, J. Lee, A. Lodi, and P. Toth. 2008. Water network design by MINLP. Yorktown Heights, NY: IBM Research.
Centre for Water Systems at the University of Exeter. 2014. “Water distribution network benchmarks.” Accesed January 5, 2019. http://emps.exeter.ac.uk/engineering/research/cws/.
Deo, N. 1974. Graph theory with applications to engineering and computer science (Prentice Hall series in automatic computation). Upper Saddle River, NJ: Prentice-Hall.
Fu, G., D. Butler, and S.-T. Khu. 2008. “Multiple objective optimal control of integrated urban wastewater systems.” Environ. Modell. Software 23 (2): 225–234. https://doi.org/10.1016/j.envsoft.2007.06.003.
Fu, G., Z. Kapelan, J. Kasprzyk, and P. Reed. 2012a. “Optimal design of water distribution systems using many-objective visual analytics.” J. Water Resour. Plann. Manage. 139 (6): 624–633. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000311.
Fu, G., Z. Kapelan, and P. Reed. 2012b. “Reducing the complexity of multiobjective water distribution system optimization through global sensitivity analysis.” J. Water Resour. Plann. Manage. 138 (3): 196–207. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000171.
Gessler, J. 1985. “Pipe network optimization by enumeration.” In Computer applications in water resources, 572–581. Reston, VA: ASCE.
Johns, M. B., E. Keedwell, and D. Savic. 2014. “Adaptive locally constrained genetic algorithm for least-cost water distribution network design.” J. Hydroinf. 16 (2): 288–301. https://doi.org/10.2166/hydro.2013.218.
Kang, D., and K. Lansey. 2012. “Revisiting optimal water-distribution system design: Issues and a heuristic hierarchical approach.” J. Water Resour. Plann. Manage. 138 (3): 208–217. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000165.
Keedwell, E., and S. Khu. 2006. “Novel cellular automata approach to optimal water distribution network design.” J. Comput. Civ. Eng. 20 (1): 49–56. https://doi.org/10.1061/(ASCE)0887-3801(2006)20:1(49).
Kennedy, J., and R. Eberhart. 1995. “Particle swarm optimization.” In Vol. 1944 of Proc., ICNN’95: Int. Conf. on Neural Networks 4, 1942–1948. Piscataway, NJ: IEEE.
Meng, F., G. Fu, and D. Butler. 2016. “Water quality permitting: From end-of-pipe to operational strategies.” Water Res. 101 (Sep): 114–126. https://doi.org/10.1016/j.watres.2016.05.078.
Montalvo, I., J. Izquierdo, R. Pérez-García, and M. Herrera. 2014. “Water distribution system computer-aided design by agent swarm optimization.” Comput.-Aided Civ. Infrastruct. Eng. 29 (6): 433–448. https://doi.org/10.1111/mice.12062.
Nicklow, J., et al. 2010. “State of the art for genetic algorithms and beyond in water resources planning and management.” J. Water Resour. Plann. Manage. 136 (4): 412–432. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000053.
Ormsbee, L., and T. Walski. 2016. “Darcy-Weisbach versus Hazen-Williams: No calm in West Palm.” In Proc., World Environmental and Water Resources Congress 2016, 455–464, Reston, VA: ASCE.
Reca, J., and J. Martínez. 2006. “Genetic algorithms for the design of looped irrigation water distribution networks.” Water Resour. Res. 42 (5): W05416. https://doi.org/10.1029/2005WR004383.
Rossman, L. A. 2000. EPANET 2: Users manual. Washington, DC: USEPA.
Sadollah, A., D. G. Yoo, and J. H. Kim. 2015. “Improved mine blast algorithm for optimal cost design of water distribution systems.” Eng. Optim. 47 (12): 1602–1618. https://doi.org/10.1080/0305215X.2014.979815.
Sheikholeslami, R., A. C. Zecchin, F. Zheng, and S. Talatahari. 2015. “A hybrid cuckoo–harmony search algorithm for optimal design of water distribution systems.” J. Hydroinf. 18 (3): 544–563. https://doi.org/10.2166/hydro.2015.174.
Storn, R., and K. Price. 1997. “Differential evolution: A simple and efficient heuristic for global optimization over continuous spaces.” J. Global Optim. 11 (4): 341–359. https://doi.org/10.1023/A:1008202821328.
Sweetapple, C., G. Fu, and D. Butler. 2014. “Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions.” Water Res. 55 (May): 52–62. https://doi.org/10.1016/j.watres.2014.02.018.
Tolson, B. A., M. Asadzadeh, H. R. Maier, and A. Zecchin. 2009. “Hybrid discrete dynamically dimensioned search (HD-DDS) algorithm for water distribution system design optimization.” Water Resour. Res. 45 (12): W12416. https://doi.org/10.1029/2008WR007673.
Tolson, B. A., and C. A. Shoemaker. 2007. “Dynamically dimensioned search algorithm for computationally efficient watershed model calibration.” Water Resour. Res. 43 (1): W01413. https://doi.org/10.1029/2005WR004723.
Vairavamoorthy, K., and M. Ali. 2000. “Optimal design of water distribution systems using genetic algorithms.” Comput.-Aided Civ. Infrastruct. Eng. 15 (5): 374–382. https://doi.org/10.1111/0885-9507.00201.
Walski, T. 2015. “Real-world considerations in water distribution system design.” J. Water Resour. Plann. Manage. 141 (9): 02515002. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000574.
Walski, T. M., D. V. Chase, D. A. Savic, W. Grayman, S. Beckwith, and E. Koelle. 2003. Advanced water distribution modeling and management. Waterbury, CT: Haestad Press.
Wang, Q., M. Guidolin, D. Savic, and Z. Kapelan. 2015. “Two-objective design of benchmark problems of a water distribution system via MOEAs: Towards the best-known approximation of the true Pareto front.” J. Water Resour. Plann. Manage. 141 (3): 04014060. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000460.
Wang, Y., A. S. Chen, G. Fu, S. Djordjević, C. Zhang, and D. A. Savić. 2018. “An integrated framework for high-resolution urban flood modelling considering multiple information sources and urban features.” Environ. Modell. Software 107 (Sep): 85–95. https://doi.org/10.1016/j.envsoft.2018.06.010.
Wu, Z., and T. Walski. 2005. “Self-adaptive penalty approach compared with other constraint-handling techniques for pipeline optimization.” J. Water Resour. Plann. Manage. 131 (3): 181–192. https://doi.org/10.1061/(ASCE)0733-9496(2005)131:3(181).
Wu, Z. Y., and A. R. Simpson. 2001. “Competent genetic-evolutionary optimization of water distribution systems.” J. Comput. Civ. Eng. 15 (2): 89–101. https://doi.org/10.1061/(ASCE)0887-3801(2001)15:2(89).
Zhang, C., X. Chen, Y. Li, W. Ding, and G. Fu. 2018. “Water-energy-food nexus: Concepts, questions and methodologies.” J. Cleaner Prod. 195 (Sep): 625–639. https://doi.org/10.1016/j.jclepro.2018.05.194.
Zheng, F., A. R. Simpson, and A. C. Zecchin. 2011. “A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems.” Water Resour. Res. 47 (8): W08531. https://doi.org/10.1029/2011wr010394.
Zheng, F., A. Zecchin, J. Newman, H. Maier, and G. Dandy. 2017. “An adaptive convergence-trajectory controlled ant colony optimization algorithm with application to water distribution system design problems.” IEEE Trans. Evol. Comput. 21 (5): 773–791. https://doi.org/10.1109/TEVC.2017.2682899.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 12 • December 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Nov 21, 2019
Accepted: Jun 19, 2020
Published online: Sep 28, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 28, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.