Robust Design of Water Distribution Networks for a Proactive Risk Management
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 2
Abstract
In the last three decades the optimal design of water distribution systems problem has been studied by a great many researchers, and this has resulted in the development of a large number of models and the application of optimization techniques. The design of these infrastructures is based on future predefined and perfectly known working conditions for the water distribution networks, a premise that may direct the optimization process to solutions which, although optimal for the imposed scenario, may perform badly if reality turns out to be significantly different. In fact the working conditions can be disrupted by accidents such as broken pipes or reservoirs, technical failures, change in demand, etc. In the context of a proactive attitude toward risk, it is important to consider these aspects at the design phase. This paper presents a robust optimization-based approach for designing a water distribution network aimed at obtaining solutions that can cope with the uncertainty of the network’s working conditions. Robust optimization is a scenario based technique, and in the present case its goal is to provide significant savings in comparison with the worst case scenario solution, while incurring only minor suboptimality for the rest of the scenarios, and being almost feasible for all the scenarios. The solution of the robust optimization problem is obtained with a methodology that uses the link between a simulated annealing algorithm, the optimizer, and a hydraulic simulator, here used to solve the problem’s hydraulic constraints. The application of the proposed methodology is illustrated with an example of a water distribution network.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writers gratefully acknowledge support received from the Fundação para a Ciência e a Tecnologia through Grant No. UNSPECIFIEDPTDC/ECM/64821/2006 (Project: “Integrated risk management of public infrastructures: the water supply systems”).
References
Aarts, E., and Korst, J. (1989). Simulated annealing and Boltzmann machines: A stochastic approach to combinatorial optimization and neural computing, Wiley, New York.
Afonso, P., and Cunha, M. C. (2007). “Robust optimal design of activated sludge bioreactors.” J. Environ. Eng., 133(1), 44–52.
Alperovits, E., and Shamir, U. (1977). “Design of optimal water distribution systems.” Water Resour. Res., 13(6), 885–900.
Babayan, A. V., Savic, D. A., Walters, G. A., and Kapelan, Z. S. (2007). “Robust least-cost design of water distribution networks using redundancy and integration-based methodologies.” J. Water Resour. Plann. Manage., 133(1), 67–77.
Birge, J. R. (1982). “The value of the stochastic solution in stochastic linear programs with fixed recourse.” Math. Program., 24, 314–325.
Cunha, M. C., and Sousa, J. (1999). “Water distribution network design optimization: A simulated annealing approach.” J. Water Resour. Plann. Manage., 125(4), 215–221.
Cunha, M. C., and Sousa, J. (2001). “Hydraulic infrastructures design using simulated annealing.” J. Infrastruct. Syst., 7(1), 32–39.
Daniels, R. L., and Kouvelis, P. (1995). “Robust scheduling to hedge against processing time uncertainty in single-stage production.” Manage. Sci., 41, 363–376.
Escudero, L., Quintana, F. J., and Salmeron, J. (1999). “A modeling and an algorithm framework for oil supply, transformation and distribution optimization under uncertainty.” Eur. J. Oper. Res., 114, 638–656.
Escudero, L. F., Kamesan, P. V., King, A. J., and Wets, R. J.-B. (1993). “Production planning via scenario modeling.” Ann. Operat. Res., 43, 309–335.
Ezell, B. C., Farr, J. V., and Wiese, I. (2000). “Infrastructure risk analysis model.” J. Infrastruct. Syst., 6(3), 114–117.
Farmani, R., Walters, G., and Savic, D. (2006). “Evolutionary multi-objective optimization of the design and operation of water distribution network: Total cost vs. reliability vs. water quality.” J. Hydroinform., 8(3), 165–179.
Fiering, M. B., and Matalas, N. C. (1990). “Decision making under uncertainty.” Climate change and U.S. water resources, P. E. Waggoner, ed., Wiley, New York, 75–86.
Glover, F., and Laguna, M. (1997). Tabu search, Kluwer, Dordrecht, The Netherlands.
Goldberg, D. (1989). Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, Mass.
González-Velarde, J. L., and Laguna, M. (2004). “A Benders-based heuristic for the robust capacitated international sourcing problem.” IIE Trans., 36, 1125–1133.
Grayman, W. M. (2005). “Incorporating uncertainty and variability in engineering analysis.” J. Water Resour. Plann. Manage., 131(3), 158–160.
Green, K. C., Armstrong, J. S., and Graefe, A. (2007). “Methods to elicit forecasts from groups: Delphi and prediction markets compared.” Int. J. Forecast., 8, 17–20.
Gutierrez, G. J., and Kouvelis, P. (1995). “A robustness approach to international sourcing.” Ann. Operat. Res., 59, 165–193.
Haimes, Y. Y., Matalas, N., Lambert, J. H., Jackson, B. A., and James, F. R. (1998). “Reducing vulnerability of water supply systems to attack.” J. Infrastruct. Syst., 4(4), 164–177.
Laguna, M. (1998). “Applying robust optimization to capacity expansion of one location in telecommunications with demand uncertainty.” Manage. Sci., 44, S101–S110.
Laguna, M., Lino, P., Pérez, A., Quintanilla, S., and Valls, V. (2000). “Minimizing weighted tardiness of jobs with stochastic interruptions in parallel machines.” Eur. J. Oper. Res., 127(2), 444–457.
Malcolm, S., and Zenios, S. (1994). “Robust optimization for power capacity expansion planning.” J. Oper. Res. Soc., 45, 1040–1049.
Mays, L. (1996). “The role of risk analysis in water resources engineering.” Water Resour. Update, 103, 8–12.
Mulvey, J. M., Vanderbei, R. J., and Zenios, S. A. (1995). “Robust optimization of large-scale systems.” Oper. Res., 43(2), 264–281.
Paraskevopoulos, D., Karakitsos, E., and Rustem, B. (1991). “Robust capacity planning under uncertainty.” Manage. Sci., 37(7), 787–800.
Peterson, C., and Soderberg, B. (1997). “Artificial neural networks.” Local search in combinatorial optimization, E. Aarts and J. K. Lenstra, eds., Wiley, New York, 173–213.
Ricciardi, K. L., Pinder, G. F., and Karatzas, G. P. (2007). “Efficient groundwater system design subject to uncertainty using robust optimization.” J. Water Resour. Plann. Manage., 133(3), 253–263.
Rogers, P. P., and Fiering, M. B. (1986). “Use of systems analysis in water management.” Water Resour. Res., 22(9S), 146S–158S.
Shinstine, D. S., Iftekhar, A., and Lansey, K. E. (2002). “Reliability/availability analysis of municipal water distribution networks: Case studies.” J. Water Resour. Plann. Manage., 128(2), 140–151.
Snyder, L. V. (2006). “Facility location under uncertainty: A review.” IIE Trans., 38(7), 547–564.
Vamvakeridou-Lyroudia, L. S., Savic, D. A., and Walters, G. A. (2006). “Fuzzy hierarchical decision support system for water distribution network optimization.” Civ. Eng. Environ. Syst., 23(3), 237–261.
Walski, T. M. (1994). Valves and water distribution system reliability, Proc., AWWA National Convention, AWWA, New York.
Walski, T. M., et al. (1987). “Battle of the network models: Epilogue.” J. Water Resour. Plann. Manage., 113(2), 191–203.
Walski, T. M., Chase, D., Savic, D., Grayman, W., Beckwith, S., and Kolle, E. (2003). Advance water distribution modeling and management, Bentley Systems, Exton, Pa.
Walski, T. M., and Gessler, J. (1984). “Selecting optimal strategy for distribution system expansion and reinforcement.” Proc., Urban Water ‘84.
Walski, T. M., and Gessler, J. (1988). “Selecting optimal pipe sizes for water distribution systems.” Opflow (AWWA), 80(2), 35.
Watkins, D. W., Jr., and McKinney, D. C. (1997). “Finding robust solutions to water resources problems.” J. Water Resour. Plann. Manage., 123(1), 49–58.
Xu, C., and Goulter, I. C. (1999). “Reliability-based optimal design of water distribution networks.” J. Water Resour. Plann. Manage., 125(6), 352–362.
Yamashita, D. S., Armentano, V. A., and Laguna, M. (2007). “Robust optimization models for project scheduling with resource availability cost.” Journal of Scheduling, 10(1), 67–76.
Yu, C. -S., and Li, H. -L. (2000). “A robust optimization model for stochastic logistic problems.” Int. J. Prod. Econ., 64, 385–397.
Information & Authors
Information
Published In
Copyright
© 2010 ASCE.
History
Received: Sep 25, 2008
Accepted: Apr 3, 2009
Published online: Feb 12, 2010
Published in print: Mar 2010
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.