Technical Papers
Sep 23, 2024

Robust and Reliable Design Alternatives to Water Distribution Networks: Introducing a Penalty-Free Hybrid Metaheuristic Multiobjective Algorithm with a Posterior Performance Investigation Model

Publication: Journal of Water Resources Planning and Management
Volume 150, Issue 12

Abstract

The present study introduces a novel penalty-free hybrid metaheuristic, differential evolution–krill herd algorithm (DE-KHA) a multiobjective algorithm (MOA) for the reliability-based optimal design of water distribution networks (WDNs). The selection mechanism of the DE-KHA MOA is equipped with nondominated sorting and density estimation schemes to obtain a Pareto front with diverse trade-off solutions. The introduced penalty-free scheme allows the algorithm to search for hydraulically functional nondominant solutions. With this implemented framework of the DE-KHA MOA, the WDN design problem is formulated with two conflicting objectives, (1) minimizing pipe investment cost; and (2) maximizing network’s reserve through flow entropy (SF), a surrogate reliability measure. The application and computational efficiency of the proposed MOA are demonstrated by employing two well-established benchmark case studies. Parallelly a trial-based approach for conducting sensitivity analysis for MOAs is demonstrated. The computational results manifest the efficacy of the penalty-free DE-KHA MOA in resulting in the Pareto front comprising the hydraulic feasible nondominant solutions of disparate trade-off relationships. As well, the results highlight the applicability of the proposed sensitivity analysis approach in improving the convergence behavior of the MOA. Following the reliability-based design, to assess the flexibility of the solved nondominant solutions under critical scenarios above design standards, the study performed a posterior performance investigation using pressure-driven analysis. The results demonstrate the effectiveness of the proposed approach with supported subjective knowledge in selecting robust design alternatives that are mechanically and hydraulically reliable. Moreover, the proposed approach eases the effort and perplexing state of handling increased nondominant design options with larger-size WDNs.

Practical Applications

The present study introduces a computationally efficient multiobjective algorithm for the economical and reliable design of water distribution networks. By considering the reliability measure (flow entropy) in the design framework, the study focuses on proposing design alternatives for water utilities with inherent redundancy and tolerance to failures (mechanical). Following optimal design, the study proposes a performance investigation model that is useful in assessing the network’s integrity, detailing the quantitative and qualitative performance of alternate designs in the face of uncertainties. This particular framework is notably more useful in proposing water utilities, a set of economical yet robust (flexible) design alternatives, which quickly adapt to uncertainties. As well, the proposed design approach eases the effort of designers in handling the increased design options with larger-size networks.

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 codes that support the findings of the study are available from the corresponding author upon request.

References

Alperovits, E., and U. Shamir. 1977. “Design of optimal water distribution systems.” Water Resour. Res. 13 (6): 885–900. https://doi.org/10.1029/WR013i006p00885.
Atkinson, S., R. Farmani, F. A. Memon, and D. Butler. 2014. “Reliability indicators for water distribution system design: Comparison.” J. Water Resour. Plann. Manage. 140 (2): 160–168. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000304.
Awumah, K., I. Goulter, and S. K. Bhatt. 1991. “Entropy-based redundancy measures in water distribution networks.” J. Hydraul. Eng. 117 (5): 595–614. https://doi.org/10.1061/(ASCE)0733-9429(1991)117:5(595).
Babayan, A. V., D. A. Savic, G. A. Walters, and Z. S. Kapelan. 2007. “Robust least-cost design of water distribution networks using redundancy and integration-based methodologies.” J. Water Resour. Plann. Manage. 133 (1): 67–77. https://doi.org/10.1061/(ASCE)0733-9496(2007)133:1(67).
Babu, K. S. J., and D. P. Vijayalakshmi. 2012. “Self-adaptive PSO-GA hybrid model for combinatorial water distribution network design.” J. Pipeline Syst. Eng. Pract. 4 (1): 57–67. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000113.
Baños, R., J. Reca, J. Martínez, C. Gil, and A. L. Márquez. 2011. “Resilience indexes for water distribution network design: A performance analysis under demand uncertainty.” Water Resour. Manage. 25 (10): 2351–2366. https://doi.org/10.1007/s11269-011-9812-3.
Barlow, E., and T. T. Tanyimboh. 2014. “Multiobjective memetic algorithm applied to the optimisation of water distribution systems.” Water Resour. Manage. 28 (8): 2229–2242. https://doi.org/10.1007/s11269-014-0608-0.
Bin Mahmoud, A. A., and K. R. Piratla. 2018. “Comparative evaluation of resilience metrics for water distribution systems using a pressure driven demand-based reliability approach.” J. Water Supply: Res. Technol.—AQUA 67 (6): 517–530. https://doi.org/10.2166/aqua.2018.010.
Cheung, P. B., L. F. R. Reis, K. T. M. Formiga, F. H. Chaudhry, and W. G. C. Ticona. 2003. “Multiobjective evolutionary algorithms applied to the rehabilitation of a water distribution system: A Comparative study.” In Proc., Evolutionary Multi-Criterion Optimization: Second Int. Conf., EMO 2003, Faro, Portugal, April 8–11, 2003, 662–676. Berlin: Springer.
Creaco, E., A. Fortunato, M. Franchini, and M. R. Mazzola. 2014a. “Comparison between entropy and resilience as indirect measures of reliability in the framework of water distribution network design.” Procedia Eng. 70 (Jan): 379–388. https://doi.org/10.1016/j.proeng.2014.02.043.
Creaco, E., and M. Franchini. 2012. “Fast network multiobjective design algorithm combined with an a posteriori procedure for reliability evaluation under various operational scenarios.” Urban Water J. 9 (6): 385–399. https://doi.org/10.1080/1573062X.2012.690432.
Creaco, E., M. Franchini, and E. Todini. 2016. “Generalized resilience and failure indices for use with pressure-driven modeling and leakage.” J. Water Resour. Plann. Manage. 142 (8): 04016019. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000656.
Creaco, E., M. Franchini, and T. M. Walski. 2014b. “Taking account of uncertainty in demand growth when phasing the construction of a water distribution network.” J. Water Resour. Plann. Manage. 141 (2): 04014049. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000441.
Cunha, M., and J. Marques. 2020. “A new multiobjective simulated annealing algorithm-MOSA-GR: Application to the optimal design of water distribution networks.” Water Resour. Res. 56 (3): e2019WR025852. https://doi.org/10.1029/2019WR025852.
Cunha, M., J. Marques, E. Creaco, and D. Savic. 2019. “A dynamic adaptive approach for water distribution network design.” J. Water Resour. Plann. Manage. 145 (7): 04019026. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001085.
Dandy, G. C., and M. O. Engelhardt. 2006. “Multiobjective trade-offs between cost and reliability in the replacement of water mains.” J. Water Resour. Plann. Manage. 132 (2): 79–88. https://doi.org/10.1061/(ASCE)0733-9496(2006)132:2(79).
Deb, K. 2011. Multiobjective optimization using evolutionary algorithms: An introduction. London: Springer.
Deb, K. 2012. Optimization for engineering design algorithms and examples. New Delhi, India: PHI Learning Private Limited.
Ezzeldin, R., M. Zelenakova, H. F. Abd-Elhamid, K. Pietrucha-Urbanik, and S. Elabd. 2023. “Hybrid optimization algorithms of firefly with GA and PSO for the optimal design of water distribution networks.” Water 15 (10): 1906. https://doi.org/10.3390/w15101906.
Ezzeldin, R. M., and B. Djebedjian. 2020. “Optimal design of water distribution networks using whale optimization algorithm.” Urban Water J. 17 (1): 14–22. https://doi.org/10.1080/1573062X.2020.1734635.
Fallah, H. S., S. Ghazanfari, C. R. Suribabu, and E. Rashedi. 2021. “Optimal pipe dimensioning in water distribution networks using gravitational search algorithm.” ISH J. Hydraul. Eng. 27 (S1): 242–255. https://doi.org/10.1080/09715010.2019.1624630.
Farmani, R., G. Walters, and D. Savic. 2007. “Evolutionary multiobjective optimization of the design and operation of water distribution network: Total cost vs. reliability vs. water quality.” J. Hydroinf. 8 (3): 165–179. https://doi.org/10.2166/hydro.2006.019b.
Farmani, R., G. A. Walters, and D. A. Savic. 2005. “Trade-off between total cost and reliability for anytown water distribution network.” J. Water Resour. Plann. Manage. 131 (3): 161–171. https://doi.org/10.1061/(ASCE)0733-9496(2005)131:3(161).
Fujiwara, O., and D. B. Khang. 1990. “A two-phase decomposition method for optimal design of looped water distribution networks.” Water Resour. Res. 26 (4): 539–549. https://doi.org/10.1029/WR026i004p00539.
Gargano, R., and D. Pianese. 2000. “Reliability as tool for hydraulic network planning.” J. Hydraul. Eng. 126 (5): 354–364. https://doi.org/10.1061/(ASCE)0733-9429(2000)126:5(354).
Greco, R., A. Di Nardo, and G. Santonastaso. 2012. “Resilience and entropy as indices of robustness of water distribution networks.” J. Hydroinf. 14 (3): 761–771. https://doi.org/10.2166/hydro.2012.037.
Hashimoto, T., J. R. Stedinger, and D. P. Loucks. 1982. “Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation.” Water Resour. Res. 18 (1): 14–20. https://doi.org/10.1029/WR018i001p00014.
Huang, Y., F. Zheng, H. F. Duan, and Q. Zhang. 2020. “Multiobjective optimal design of water distribution networks accounting for transient impacts.” Water Resour. Manage. 34 (4): 1517–1534. https://doi.org/10.1007/s11269-020-02517-4.
Liu, H., D. Savic, Z. Kapelan, M. Zhao, Y. Yuan, and H. Zhao. 2014. “A diameter-sensitive flow entropy method for reliability consideration in water distribution system design.” Water Resour. Res. 50 (7): 5597–5610. https://doi.org/10.1002/2013WR014882.
Liu, H., D. A. Savic, Z. Kapelan, E. Creaco, and Y. Yuan. 2016. “Reliability surrogate measures for water distribution system design: Comparative analysis.” J. Water Resour. Plann. Manage. 143 (2): 04016072. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000728.
Maier, H. R., A. R. Simpson, A. C. Zecchin, W. K. Foong, K. Y. Phang, H. Y. Seah, and C. L. Tan. 2003. “Ant colony optimization for design of water distribution systems.” J. Water Resour. Plann. Manage. 129 (3): 200–209. https://doi.org/10.1061/(ASCE)0733-9496(2003)129:3(200).
Marques, J., M. Cunha, and D. A. Savic. 2015. “Multi-objective optimization of water distribution systems based on a real options approach.” Environ. Modell. Software 63 (1): 1–13. https://doi.org/10.1016/j.envsoft.2014.09.014.
Montalvo, I., J. Izquierdo, S. Schwarze, and R. Pérez-García. 2010. “Multiobjective particle swarm optimization applied to water distribution systems design: An approach with human interaction.” Math. Comput. Modell. 52 (7–8): 1219–1227. https://doi.org/10.1016/j.mcm.2010.02.017.
Moosavian, N., and B. J. Lence. 2019. “Fittest individual referenced differential evolution algorithms for optimization of water distribution networks.” J. Comput. Civ. Eng. 33 (6): 04019036. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000849.
Neelakantan, T. R., and K. Rohini. 2021. “Simplified pressure-driven analysis of water distribution network and resilience estimation.” J. Water Resour. Plann. Manage. 147 (3): 06021002. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001349.
Ostfeld, A. 2004. “Reliability analysis of water distribution systems.” J. Hydroinf. 6 (4): 281–294. https://doi.org/10.2166/hydro.2004.0021.
Palod, N., V. Prasad, and R. Khare. 2022. “A new multiobjective evolutionary algorithm for the optimization of water distribution networks.” Water Supply 22 (12): 8972–8987. https://doi.org/10.2166/ws.2022.413.
Perelman, L., A. Ostfeld, and E. Salomons. 2008. “Cross entropy multiobjective optimization for water distribution systems design.” Water Resour. Res. 44 (9): W09413. https://doi.org/10.1029/2007WR006248.
Poojitha, S. N., and V. Jothiprakash. 2021. “Hybrid differential evolution and krill herd algorithm for the optimal design of water distribution networks.” J. Comput. Civ. Eng. 36 (1): 04021032. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000999.
Prasad, T., and N. Park. 2004. “Multiobjective genetic algorithms for design of water distribution networks.” J. Water Resour. Plann. Manage. 130 (1): 73–82. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:1(73).
Prasad, T. D., and T. T. Tanyimboh. 2008. “Entropy based design of ‘Anytown’ water distribution network.” In Water distribution systems analysis 2008, 1–12. Reston, VA: ASCE.
Preeti, S., S. N. Poojitha, and V. Jothiprakash. 2023. “Evaluation of sustainability index of water distribution network using demand-driven and pressure-driven analysis.” J. Water Resour. Plann. Manage. 149 (3): 04023003. https://doi.org/10.1061/JWRMD5.WRENG-5705.
Raad, D. N., A. N. Sinske, and J. H. Van Vuuren. 2010. “Comparison of four reliability surrogate measures for water distribution systems design.” Water Resour. Res. 46 (5): W05524. https://doi.org/10.1029/2009WR007785.
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.
Riyahi, M. M., A. E. Bakhshipour, and A. Haghighi. 2023. “Probabilistic warm solutions-based multiobjective optimization algorithm, application in optimal design of water distribution networks.” Sustainable Cities Soc. 91 (Apr): 104424. https://doi.org/10.1016/j.scs.2023.104424.
Sheikholeslami, R., and S. Talatahari. 2016. “Developed swarm optimizer: A new method for sizing optimization of water distribution systems.” J. Comput. Civ. Eng. 30 (5): 1–11. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000552.
Su, Y., L. W. Mays, N. Duan, and K. E. Lansey. 1987. “Reliability-based optimization model for water distribution systems.” J. Hydraul. Eng. 113 (12): 1539–1556. https://doi.org/10.1061/(ASCE)0733-9429(1987)113:12(1539).
Tanyimboh, T. T. 2017. “Informational entropy: A failure tolerance and reliability surrogate for water distribution networks.” Water Resour. Manage. 31 (10): 3189–3204. https://doi.org/10.1007/s11269-017-1684-8.
Tanyimboh, T. T., and A. M. Czajkowska. 2021. “Entropy maximizing evolutionary design optimization of water distribution networks under multiple operating conditions.” Environ. Syst. Decis. 41 (2): 267–285. https://doi.org/10.1007/s10669-021-09807-1.
Tanyimboh, T. T., and A. B. Templeman. 1993. “Calculating maximum entropy flows in networks.” J. Oper. Res. Soc. 44 (4): 383–396. https://doi.org/10.1057/jors.1993.68.
Tanyimboh, T. T., and A. B. Templeman. 2000. “A quantified assessment of the relationship between the reliability and entropy of water distribution systems.” Eng. Optim. 33 (2): 179–199. https://doi.org/10.1080/03052150008940916.
Todini, E. 2000. “Looped water distribution networks design using a resilience index based heuristic approach.” Urban Water 2 (2): 115–122. https://doi.org/10.1016/S1462-0758(00)00049-2.
Vairavamoorthy, K. 1994. “Water distribution networks: Design and control for intermittent supply.” Ph.D. thesis, Dept. of Civil and Environmental Engineering, Imperial College of Science, Technology and Medicine.
Wagner, B. J. M., U. Shamir, and D. H. Marks. 1988. “Water distribution reliability: Analytical methods.” J. Water Resour. Plann. Manage. 114 (3): 253–275. https://doi.org/10.1061/(ASCE)0733-9496(1988)114:3(253).
Walski, T. M. 2001. “The wrong paradigm—Why water distribution optimization doesn’t work.” J. Water Resour. Plann. Manage. 127 (4): 203–205. https://doi.org/10.1061/(ASCE)0733-9496(2001)127:4(203).
Wang, Q., M. Guidolin, D. Savic, and Z. Kapelan. 2014. “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, Q., D. A. Savić, and Z. Kapelan. 2017. “GALAXY: A new hybrid MOEA for the optimal design of water distribution systems.” Water Resour. Res. 53 (3): 1997–2015. https://doi.org/10.1002/2016WR019854.

Information & Authors

Information

Published In

Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 150Issue 12December 2024

History

Received: Oct 2, 2023
Accepted: Jun 14, 2024
Published online: Sep 23, 2024
Published in print: Dec 1, 2024
Discussion open until: Feb 23, 2025

Permissions

Request permissions for this article.

Authors

Affiliations

Assistant Professor, Dept. of Civil Engineering, National Institute of Technology Calicut, Kozhikode, Kerala 673601, India. ORCID: https://orcid.org/0000-0003-2721-9224. Email: [email protected]; [email protected]
Professor, Dept. of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra 400076, India (corresponding author). ORCID: https://orcid.org/0000-0002-0303-2468. Email: [email protected]

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.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share