Skip to main content

Advertisement

SpringerLink
Log in

Design Optimization of Water Distribution Networks with Dynamic Search Space Reduction GA

  • Published:
Water Resources Management Aims and scope Submit manuscript

A Correction to this article was published on 01 February 2024

This article has been updated

Abstract

Evolutionary algorithms (EAs) have been used extensively for the optimal design of water distribution networks (WDNs). There is evidence in the literature that search space reduction is highly effective. However, practical methods that do not introduce extra computational requirements are lacking. A dynamic search space reduction methodology is proposed to search the entire solution space without eliminating any part of the search space beforehand. The proposed methodology works on the information explored during the execution of the algorithm. Further, a self-adaptive penalty is suggested which is based on both flow and pressure deficits instead of only pressure deficit and is obtained using pressure dependent analysis. In this study, the methodology is demonstrated using a Genetic Algorithm (GA). The effectiveness of the methodology is demonstrated on the Ramnagar Network of Nagpur City, India and two benchmark problems from the literature. The proposed methodology resulted in a substantial reduction in the computational efforts and provided nine improved solutions as compared to the best solution available in the literature for one of the networks. The techniques proposed are generic and can be incorporated in other EAs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

All relevant data are included in the paper or its supplementary material. EPANET input files for the example network is available with the first author and can be shared on request.

Change history

References

  • Abdy Sayyed MAH, Gupta R, Tanyimboh TT (2015) Noniterative application of EPANET for pressure dependent modelling of water distribution systems. Water Resour Manag 29(9):3227–3242. https://doi.org/10.1007/s11269-015-0992-0

  • Abdy Sayyed MAH, Gupta R, Tanyimboh TT (2019) Combined flow and pressure deficit-based penalty in GA for optimal design of water distribution network. ISH J Hydraul Engg. https://doi.org/10.1080/09715010.2019.1604180

  • Barlow E, Tanyimboh TT (2014) Multi-objective memetic algorithm applied to the optimisation of water distribution systems. Water Resour Manag 28(8):2229–2242. https://doi.org/10.1007/s11269-014-0608-0

    Article  Google Scholar 

  • Bhave PR (2003) Optimal design of water distribution networks. Narosa Publishing House Pvt. Ltd., New Delhi, India; and Alpha Science International Ltd., Pangbourne, UK 

    Google Scholar 

  • Bhave PR, Gupta R (2006) Analysis of Water Distribution Networks. Narosa Publishing House Pvt. Ltd., New Delhi, India; and Alpha Science International Ltd., Pangbourne, UK 

    Google Scholar 

  • Chandapillai J (1991) Realistic simulation of water distribution system. J Transp Engg 117(2):258–263

    Article  Google Scholar 

  • Coelho B, Andrade-Campos A (2012) Using different strategies for improving efficiency in water supply systems. Proceedings of the 1st ECCOMAS Young Investigators Conference, Aveiro, Portugal. Universidade de Aveiro

  • Czajkowska AM (2016) Maximum Entropy Based Evolutionary Optimization of Water Distribution Networks Under Multiple Operating Conditions and Self-Adaptive Search Space Reduction Method. PhD thesis. University of Strathclyde, Glasgow, UK

  • El-Ghandour HA, Elbeltagi E (2018) Comparison of Five Evolutionary Algorithms for Optimization of Water Distribution Networks. J Comput Civ Eng 32(1). https://doi.org/10.1061/(asce)cp.1943-5487.0000717

  • Geem ZW (2006) Optimal cost design of water distribution networks using harmony search. Eng Optim 38(3):259–277. https://doi.org/10.1080/03052150500467430

    Article  Google Scholar 

  • Gupta R, Abdy Sayyed MAH, Tanyimboh TT (2018) Discussion of new pressure-driven approach for modeling water distribution networks by Herman A. Mahmoud, Dragan Savic and Zoran Kapelan. J Water Res Pl-ASCE 144(6). https://doi.org/10.1061/(ASCE)WR.1943‐5452.0000932

  • Gupta R, Bhave PR (1996) Comparison of methods for predicting deficient network performance. J Water Res Pl-ASCE 122(3):214–217

    Article  Google Scholar 

  • Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison- Wesley

  • Haghighi A, Samani HM, Samani ZM (2011) GA-ILP method for optimization of water distribution networks. Water Resour Manag 25(7):1791–1808

    Article  Google Scholar 

  • Hong SPV, Thanh VN (2022) Application of artificial intelligence algorithm to optimize the design of water distribution system. Int J Constr Manag 1–11. https://doi.org/10.1080/15623599.2022.2101593

  • Jabbary A, Podeh HT, Younesi H et al (2016) Development of central force optimization for pipe-sizing of water distribution networks. Water Sci Technol Water Supply 16(5):1398–1409. https://doi.org/10.2166/ws.2016.051

    Article  Google Scholar 

  • Jain P, Khare R (2021) Application of Parameter-Less Rao Algorithm in Optimization of Water Distribution Networks Through Pressure-Driven Analysis. Water Resour Manag 35:4067–4084

    Article  Google Scholar 

  • Jaynes ET (1957) Information theory and statistical mechanics. Phys Rev 106: 620–630 and 108:171–190

  • Kadu MS, Gupta R, Bhave PR (2008) Optimal design of water networks using a modified genetic algorithm with reduction in search space. J Water Res Pl-ASCE 134(2):147–160

    Article  Google Scholar 

  • Kim JH, Kim TG, Kim JH et al (1994) A study on the pipe network system design using non-linear programming. J Korean Water Resour Ass 27(4):59–67

    Google Scholar 

  • Mala-Jetmarova H, Sultanova N, Savic D (2018) Lost in optimisation of water distribution systems? A literature review of system design. Water (Switzerland) MDPI AG. https://doi.org/10.3390/w10030307

  • Marchi A, Dandy G, Wilkins A et al (2014) Methodology for Comparing Evolutionary Algorithms for Optimization of Water Distribution Systems. J Water Res Pl-ASCE 140(1):22–31. https://doi.org/10.1061/(asce)wr.1943-5452.0000321

    Article  Google Scholar 

  • Moosavian N, Lence B (2018) Testing evolutionary algorithms for optimization of water distribution networks. Can J Civ Engg 46(5):391–402. https://doi.org/10.1139/cjce-2018-0137

    Article  Google Scholar 

  • Murphy LJ, Simpson AR (1992) Genetic Algorithms in Pipe Network Optimization, Research Report No. R93, Department of Civil and Environmental Engineering, University of Adelaide, Australia

  • Palod N, Prasad V, Khare R (2021) Redefining the application of an evolutionary algorithm for the optimal pipe sizing problem. J Water and Clim Change 12(6):2299–2313

    Article  Google Scholar 

  • Pankaj B, Naidu M, Vasan A et al (2020) Self-adaptive cuckoo search algorithm for optimal design of water distribution systems. Water Resour Manage 34:3129–3146

    Article  Google Scholar 

  • Reca J, Martinez J, Lopez R (2017) A hybrid water distribution networks design optimization method based on a search space reduction approach and a genetic algorithm. Water 9(11):845. https://doi.org/10.3390/w9110845

    Article  Google Scholar 

  • Rossman LA (2000) EPANET 2 user’s manual, Water Supply and Water Resources Division, National Risk Management Research Laboratory, Cincinnati. OH

  • Saleh SH, Tanyimboh TT (2014) Optimal design of water distribution systems based on entropy and topology. Water Resour Manag 28(11):3555–3575. https://doi.org/10.1007/s11269-014-0687-y

    Article  Google Scholar 

  • Sankaranarayanan S, Swaminathan G, Sivakumaran N et al (2017) A novel hybridized grey wolf optimization for a cost optimal design of water distribution network. Computing Conference, London, UK: 961–970. https://doi.org/10.1109/SAI.2017.8252210

  • Sarbu I, Tokar A (2018) Water distribution systems: Numerical modelling and optimisation. Polytechnic Publishing House

  • Siew C, Tanyimboh TT (2012) Penalty-free feasibility boundary convergent multi-objective evolutionary algorithm for the optimization of water distribution systems. Water Resour Manag 26(15):4485–4507. https://doi.org/10.1007/s11269-012-0158-2

    Article  Google Scholar 

  • Siew C, Tanyimboh TT, Seyoum AG (2014) Assessment of penalty-free multi-objective evolutionary optimization approach for the design and rehabilitation of water distribution systems. Water Resour Manag 28(2):373–389. https://doi.org/10.1007/s11269-013-04888

    Article  Google Scholar 

  • Sirsant S, Janga RM (2018) Reliability-based design of water distribution networks using self-adaptive differential evolution algorithm. ISH J Hydraul Eng 24(2):198–212. https://doi.org/10.1080/09715010.2017.1408038

    Article  Google Scholar 

  • Sirsant S, Hamouda MA, Shaaban MF et al (2022) A Chaotic Sobol Sequence-based multi-objective evolutionary algorithm for optimal design and expansion of water networks. Sustain Cities Soc 87. https://doi.org/10.1016/j.scs.2022.104215

  • Sivakumar P, Gorev NB, Nivedita S et al (2023) An assessment of the artificial modelling elements approach to the pressure-driven analysis of water distribution networks. Water Supply 23(5):1810–1826. https://doi.org/10.2166/ws.2023.092

    Article  Google Scholar 

  • Tanyimboh TT (2021) Redundant binary codes in genetic algorithms: multi-objective design optimization of water distribution. J Water Supply 21(1):444–457. https://doi.org/10.2166/ws.2020.329

    Article  Google Scholar 

  • Tanyimboh TT, Czajkowska AM (2018) Self-Adaptive Solution-Space Reduction Algorithm for Multi-Objective Evolutionary Design Optimization of Water Distribution Networks. Water Resour Manage 32:3337–3352. https://doi.org/10.1007/s11269-018-1994-5

    Article  Google Scholar 

  • Vairavamoorthy K, Ali M (2005) Pipe index vector: a method to improve genetic-algorithm-based pipe optimization. J Hydraul Eng 131:1117–1125. https://doi.org/10.1061/(ASCE)0733-9429(2005)131:12(1117)

    Article  Google Scholar 

  • Wagner JM, Shamir U, Marks DH (1988) Water distribution reliability: simulation method. J Water Res Pl-ASCE 114(3):276–294

    Article  Google Scholar 

  • Walski TM, Chase DV, Savic Da et al (2003) Advanced water distribution modeling and management. Heastad Press

  • Wu ZY, Walski T (2005) Self-adaptive penalty approach compared with other constraint-handling techniques for pipeline optimization. J Water Res Pl-ASCE 131. https://doi.org/10.1061/(ASCE)0733-9496(2005)131:3(181)

  • Zecchin AC, Maier HR, Simpson AR, Leonard M, Nixon JB (2007) Ant colony optimization applied to water distribution system design: A comparative study of five algorithms. J Water Res Pl-ASCE 133(1):87–92

    Article  Google Scholar 

  • Zheng F, Simpson AR, Zecchin AC (2011) A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems. Water Resour Res 47:W08531. https://doi.org/10.1029/2011WR010394

    Article  ADS  Google Scholar 

Download references

Funding

The authors received no specific funding for preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur, 440013, India

    Laxmi Gangwani

  2. Department of Civil Engineering, Visvesvaraya National Institute of Technology (VNIT), Nagpur, 440010, India

    Shilpa Dongre & Rajesh Gupta

  3. Centre for Urban Science and Engineering, Indian Institute of Technology Bombay (IITB), Powai, Mumbai, 400 076, India

    Mohd Abbas H. Abdy Sayyed

  4. School of Civil and Environmental Engineering, University of the Witwatersrand, Johannesburg, Private Bag 3, WITS, 2050, South Africa

    Tiku Tanyimboh

Authors
  1. Laxmi Gangwani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shilpa Dongre
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rajesh Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mohd Abbas H. Abdy Sayyed
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tiku Tanyimboh
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LRG, SD and RG conceptualised the study and developed the methodology, MAHAS helped in developing the computer code, LRG prepared first draft of the manuscript; RG, SD and TTT contributed in the analysis and manuscript preparation. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Rajesh Gupta.

Ethics declarations

Conflict Interests

All authors declared no conflict of interest.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlights

• A novel dynamic search space reduction methodology increases the efficiency of GA.

• New superior solutions achieved for a benchmark network.

• The proposed methodology is generic and can be used with other EAs.

The original online version of this article was revised: In this article ref. Palod et al. 2021 was incorrect and should have been ’Palod N, Prasad V, Khare R (2021) Redefining the application of an evolutionary algorithm for the optimal pipe sizing problem. J Water and Clim Change 12(6):2299–2313

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 822 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gangwani, L., Dongre, S., Gupta, R. et al. Design Optimization of Water Distribution Networks with Dynamic Search Space Reduction GA. Water Resour Manage 38, 63–79 (2024). https://doi.org/10.1007/s11269-023-03648-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-023-03648-0

Keywords

Search

Navigation