Technical Papers
Jul 14, 2015

Cost Gradient–Based Assessment and Design Improvement Technique for Water Distribution Networks with Varying Loads

Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 1

Abstract

A gradient-based network assessment is proposed as a way to understand and improve the cost and hydraulic performance of distribution networks. It seeks to reduce the computation time of optimizing water distribution networks with varying demands by using a sequence of shorter time cycles to approximate a fuller range of costs. To allow system evolution, diameters are adjusted after each cycle according to anticipated capital, energy, and damage costs. Accounting for risks of low- and high-pressure hydraulic failure not only adds needed redundancy to the network, but also helps guide the gradient search. The method was applied to the well-known network of “Anytown.” Results indicate that the technique can be effectively applied to different scenarios and generate robust solutions. Furthermore, its lower computational intensity should facilitate its application as part of a broader optimization process and thus better enable the assessment of more storage, pumping, and control alternatives.

Get full access to this article

View all available purchase options and get full access to this article.

References

Alperovits, E., and Shamir, U. (1977). “Design of optimal water distribution systems.” Water Resour. Res., 13(6), 885–900.
Babayan, A., Kapelan, Z., Savic, D., and Walters, G. (2005). “Least-cost design of water distribution networks under demand uncertainty.” J. Water Resour. Plann. Manage., 375–382.
Brill, E. D., Liebman, J. C., and Lee, H. L. (1985). “Optimization of looped water distribution networks.” Computer applications in water resources, H. C. Torno, ed., ASCE, New York, 569–571.
Corne, D. W., Jerram, N., Knowles, J. D., and Oates, M. J. (2001). “PESA-II: Region-based selection in multiobjective optimization.” Proc., Genetic and Evolutionary Computation Conf. (GECCO), Vol. 1, Association for Computing Machinery, New York, 283–290.
Creaco, E., Franchini, M., and Todini, E. (2014a). “The combined use of resilience and loop diameter uniformity as a good indirect measure of network reliability.” Urban Water J., 10–15.
Creaco, E., Franchini, M., and Walski, T. (2014b). “Accounting for phasing of construction within the design of water distribution networks.” J. Water Resour. Plann. Manage., 598–606.
Creaco, E., Franchini, M., and Walski, T. (2014c). “Taking account of uncertainty in demand growth when phasing the construction of a water distribution network.” J. Water Resour. Plann. Manage., 04014049.
di Pierro, F., Khu, S. T., Savic, D., and Berardi, L. (2009). “Efficient multi-objective optimal design of water distribution networks on a budget of simulations using hybrid algorithms.” Environ. Model. Software, 24(2), 202–213.
Eusuff, M. M., and Lansey, K. E. (2003). “Optimization of water distribution network design using the shuffled frog leaping algorithm.” J. Water Resour. Plann. Manage., 210–225.
Farmani, R., Walters, G. A., and Savic, D. A. (2005). “Trade-off between total cost and reliability for Anytown water distribution network.” J. Water Resour. Plann. Manage., 161–171.
Filion, Y. R., Adams, B. J., and Karney, B. W. (2007). “Stochastic design of water distribution systems with expected annual damages.” J. Water Resour. Plann. Manage., 244–252.
Fu, G., Kapelan, Z., Kasprzyk, J., and Reed, P. (2013). “Optimal design of water distribution systems using many-objective visual analytics.” J. Water Resour. Plann. Manage., 624–633.
Fu, G., Kapelan, Z., and Reed, P. (2012). “Reducing the complexity of multiobjective water distribution system optimization through global sensitivity analysis.” J. Water Resour. Plann. Manage., 196–207.
Fujiwara, O., and Khang, D. B. (1990). “A two-phase decomposition method for optimal design of looped water distribution networks.” Water Resour. Res., 26(4), 539–549.
Gessler, J. (1985). “Pipe network optimization by enumeration.” Computer applications in water resources, H. C. Torno, ed., ASCE, New York, 572–581.
Giacomini, M. H., Kanta, L., and Zechman, E. M. (2013). “Complex adaptive systems approach to simulate the sustainability of water resources and urbanization.” J. Water Resour. Plann. Manage., 554–564.
Gomes, H. P., Bezerra, S. T. M., Carvalho, P. S. O., and Salvino, M. M. (2009). “Optimal dimensioning model of water distribution systems.” Water SA, 35(4), 421–431.
Haghighi, A., Samani, H. M. V., and Samani, Z. M. V. (2011). “GA-ILP method for optimization of water distribution networks.” Water Resour. Manage., 25(7), 1791–1808.
Knowles, J. (2006). “ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems.” IEEE Trans. Evol. Comput., 10(1), 50–66.
Kollat, J. B., and Reed, P. M. (2006). “Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design.” Adv. Water Resour., 29(6), 792–807.
Marques, J., Cunha, M., and Savic, D. (2014). “Using real options in the optimal design of water distribution networks.” J. Water Resour. Plann. Manage., 04014052.
Michalski, R. (2000). “Learnable evolution model: Evolutionary processes guided by machine learning.” Mach. Learn., 38(1–2), 9–40.
Monbaliu, J., Jo, J. H., Fraisse, C. W., and Vadas, R. G. (1990). “Computer aided design of pipe networks.” Water resource systems application, S. P. Simonovic, I. C. Goulter, D. H. Burn, and B. J. Lence, eds., Friesen Printers, Winnipeg, Canada.
Montalvo, I., Izquierdo, J., Pérez, R., and Iglesias, P. L. (2008). “A diversity-enriched variant of discrete PSO applied to the design of water distribution networks.” Eng. Optim., 40(7), 655–668.
Morgan, D. R., and Goulter, I. C. (1985). “Water distribution design with multiple demands.” Computer applications in water resources, H. C. Torno, ed., ASCE, New York, 582–590.
Ormsbee, L. (1985). “OPNET: A nonlinear design algorithm for hydraulic networks.” Computer applications in water resources, H. C. Torno, ed., ASCE, New York, 739–748.
Ostfeld, A. (2012). “Optimal reliable design and operation of water distribution systems through decomposition.” Water Resour. Res., 48(10), W10521.
Reca, J., and Martinez, J. (2006). “Genetic algorithms for the design of looped irrigation water distribution networks.” Water Resour. Res., 42(5), W05416.
Rossman, L. A. (2000). “EPANET 2 users manual.” National Risk Management Research Laboratory, Cincinnati, OH.
Samani, H. M. V., and Naeeni, S. T. (1996). “Optimization of water distribution networks.” J. Hydraul. Res., 34(5), 623–632.
Savic, D., and Walters, G. A. (1997). “Genetic algorithms for least-cost design of water distribution networks.” J. Water Resour. Plann. Manage., 67–77.
Schaake, J., and Lai, D. (1969). “Linear programming and dynamic programming applications to water distribution network design.”, Dept. of Civil Engineering, Massachusetts Institute of Technology, Cambridge, MA.
Sharp, W. W., and Walski, T. M. (1988). “Predicting internal roughness in water mains.” Am. Water Works Assoc. J., 8(11), 34–40.
Simpson, A. R., Dandy, G. C., and Murphy, L. J. (1994). “Genetic algorithms compared to other techniques for pipe optimization.” J. Water Resour. Plann. Manage., 423–443.
Sobol’, I. M. (2001). “Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates.” Math. Comput. Simul., 55(1–3), 271–280.
Todini, E. (2000). “Looped water distribution networks design using a resilience index based heuristic approach.” Urban Water, 2(2), 115–122.
Tolson, B. A., Asadzadeh, M, Maier, H., and Zecchin, A. (2009). “Hybrid discrete dynamically dimensioned search (HD-DDS) algorithm for water distribution system design optimization.” Water Resour. Res., 45(12), W12416.
Tolson, B. A., Maier, H. R., Simpson, A. R., and Lence, B. J. (2004). “Genetic algorithms for reliability-based optimization of water distribution systems.” J. Water Resour. Plann. Manage., 63–72.
Walski, T. M. (2001). “The wrong paradigm—Why water distribution optimization doesn’t work.” J. Water Resour. Plann. Manage., 203–205.
Walski, T. M., et al. (1987). “Battle of the network models: Epilogue.” J. Water Resour. Plann. Manage., 191–203.
Walters, G. A., Hallhal, D., Savic, D., and Ouazar, D. (1999). “Improved design of ‘Anytown’ distribution network using structured messy genetic algorithms.” Urban Water, 1(1), 23–38.
Zecchin, A. C., Maier, H. R., Simpson, A. R., Leonard, M., and Nixon, J. B. (2007). “Ant colony optimization applied to water distribution system design: Comparative study of five algorithms.” J. Water Resour. Plann. Manage., 87–92.
Zheng, F., and Zecchin, A. (2014). “An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources.” Environ. Model. Software, 55, 143–155.

Information & Authors

Information

Published In

Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 142Issue 1January 2016

History

Received: Nov 5, 2014
Accepted: Jun 9, 2015
Published online: Jul 14, 2015
Discussion open until: Dec 14, 2015
Published in print: Jan 1, 2016

Permissions

Request permissions for this article.

Authors

Affiliations

Rebecca Dziedzic, Ph.D. [email protected]
Dept. of Civil Engineering, Univ. of Toronto, 35 St. George St., Toronto, ON, Canada M5S 1A4 (corresponding author). E-mail: [email protected]
Bryan W. Karney, M.ASCE
Professor, Dept. of Civil Engineering, Univ. of Toronto, 35 St. George St., Toronto, ON, Canada M5S 1A4.

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.

Cited by

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