Prioritizing Pipe Replacement: From Multiobjective Genetic Algorithms to Operational Decision Support
Publication: Journal of Water Resources Planning and Management
Volume 135, Issue 6
Abstract
Deterioration of water distribution systems and the optimal allocation of limited funds for their rehabilitation represent crucial challenges for water utility managers. Decision makers should be provided with a set of “informed” solutions to select the best rehabilitation plan with regard to available resources and management strategies. In a risk-based scenario, such an approach should result in an element-wise prioritization scheme based on individual pipe rehabilitation/replacement effectiveness. This manuscript describes a framework for devising a short-term decision support tool for pipe replacement. The approach allows for the introduction of economic, technical, and management rationales as separate objectives to produce a pipe-wise prioritization scheme which is achieved by ranking pipes selected during a multiobjective (MO) evolutionary optimization of replacement scenarios. Such a procedure helps overcome the doubts in choosing among the solutions obtained by MO evolutionary optimization due to the diverse sets of pipes selected for replacement even when they are economically comparable. The effectiveness of the entire framework is demonstrated on a real U.K. water distribution system.
Get full access to this article
View all available purchase options and get full access to this article.
References
Alvisi, S., and Franchini, M. (2005). “Rehabilitation scheduling of water distribution systems based on multiobjective genetic algorithms.” Proc., Int. Conf. on Computer and Control in Water Industry (CCWI), Vol. 2, D. A. Savic, ed., University of Exeter, Exeter, U.K., 51–56.
Andreou, S. A., Marks, D. H., and Clark, R. M. (1987a). “A new methodology for modeling break failure patterns in deteriorating water distribution systems: Theory.” Adv. Water Resour., 10(1), 2–10.
Andreou, S. A., Marks, D. H., and Clark, R. M. (1987b). “A new methodology for modeling break failure patterns in deteriorating water distribution systems: Applications.” Adv. Water Resour., 10(1), 11–20.
Berardi, L., and Kapelan, Z. (2007). “Multicase EPR strategy for the development of sewer failure performance indicators.” Proc., World Environmental and Water Resources Congress (CD-ROM), ASCE, Reston, Va.
Berardi, L., Kapelan, Z., Giustolisi, O., and Savic, D. A. (2008). “Development of pipe deterioration models for water distribution systems using EPR.” J. Hydroinform., 10(2), 113–126.
Cheung, P. B., Reis, L. F. R., Formiga, K. T. M., Chaundhry, F. H., and Ticona, W. C. (2003). “Multiobjective evolutionary algorithms applied to the rehabilitation of a water distribution system: A comparative study.” Proc., Second Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO), Vol. 2632, Springer, Berlin, 662–676.
Dandy, G. C., and Engelhardt, M. O. (2001). “The optimal scheduling of water pipe replacement using genetic algorithms.” J. Water Resour. Plann. Manage., 127(4), 214–223.
Dandy, G. C., and Engelhardt, M. O. (2006). “Multi-objective trade-offs between cost and reliability in the replacement of water mains.” J. Water Resour. Plann. Manage., 132(2), 79–88.
de Schaetzen, W., Randall-Smith, M. J., Savic, D., and Walters, G. A. (1998). “A genetic algorithm approach for rehabilitation in water supply systems.” Proc., Int. Conf. on Rehabilitation Technology for Water Industry, Society of British Water Industries, Lille, France, 1–11.
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms, Wiley, New York.
Engelhardt, M. O., Skipworth, P. J., Savic, D. A., Saul, A. J., and Walters, G. A. (2000). “Rehabilitation strategies for water distribution networks: A literature review with a UK perspective.” Urban Water, 2(2), 153–170.
Fonseca, C. M. and Fleming, P. J., and (1993). “Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization.” Proc., Fifth Int. Conf. on Genetic Algorithms, S. Forrest, ed., Morgan Kaufmann, San Mateo, Calif., 416–423.
Giustolisi, O., and Berardi, L. (2007). “Pipe level burst prediction using EPR and MCS-EPR.” Proc., Int. Conf. on Water Management Challenges in Global Change (CCWI2007 and SUWM2007), B. Ulaniki et al., eds., Taylor and Francis, London, 39–46.
Giustolisi, O., Doglioni, A., Savic, D. A., and Laucelli, D. (2004). “A proposal for an effective multi-objective non-dominated genetic algorithm: The optimised multi-objective genetic algorithm.” Rep. No. 2004/07, Univ. of Exeter, UK, ⟨www.hydroinformatics.it⟩ (Aug. 24, 2009).
Giustolisi, O., Laucelli, D., and Savic, D. A. (2006a). “Development of rehabilitation plans for water mains replacement considering risk and cost-benefit assessment.” Civ. Eng. Environ. Syst., 23(3), 175–190.
Giustolisi, O., and Savic, D. A. (2006). “A symbolic data-driven technique based on evolutionary polynomial regression.” J. Hydroinform., 8(3), 207–222.
Giustolisi, O., Savic, D. A., and Kapelan, Z. (2006b). “Multi-objective evolutionary polynomial regression.” Proc., 7th Int. Conf. on Hydroinformatics (HIC 2006), Vol. 1, P. Gourbesville et al., eds., Research Publishing Services, Chennai, India, 725–732.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, Mass.
Goulter, I. C., and Kazemi, A. (1988). “Spatial and temporal groupings of water main pipe breakage in Winnipeg.” Can. J. Civ. Eng., 15(1), 91–97.
Hadzilacos, T., Kalles, D., Preston, N., Melbourne, P., Camarinopoulos, L., Eimermacher, M., Kallidromitis, V., Frondistou-Yannas, S., Saegrov, S. (2000). “UtilNets: A water mains rehabilitation decision-support system.” Comput. Environ. Urban Syst., 24(3), 215–232.
Halhal, D., Walters, G. A., Ouzar, D., and Savic, D. A. (1997). “Water network rehabilitation with a structured messy genetic algorithm.” J. Water Resour. Plann. Manage., 123(3), 137–146.
Jacobs, P., and Karney, B. (1994). “GIS development with application to cast iron water main breakage rates.” Proc., 2nd Int. Conf. on Water Pipeline Systems, BHRA Conference Series No. 10, D. S. Miller, ed. Mech Eng. Publs., London, U.K., 53–62.
Kane, M. J. (1994). “Database to prioritise main rehabilitation.” Proc., Int Conf on of Hydrotop’94, Marseille, France, 201–213.
Kapelan, Z. (2002). “Calibration of water distribution system hydraulic models.” Ph.D. thesis, Univ. of Exeter, Exeter, U.K.
Kettler, A. J., and Goulter, I. C. (1985). “An analysis of pipe breakage in urban water distribution networks.” Can. J. Civ. Eng., 12(2), 286–293.
Kim, J. H., and Mays, L. W. (1994). “Optimal rehabilitation model for water distribution systems.” J. Water Resour. Plann. Manage., 120(5), 674–692.
Kleiner, Y., Adams, B. J., and Rogers, J. S. (1998). “Selection and scheduling of rehabilitation alternatives for water distribution systems.” Water Resour. Res., 34(8), 2053–2061.
Kleiner, Y., and Rajani, B. B. (2001). “Comprehensive review of structural deterioration of water mains: Statistical models.” Urban Water, 3(3), 131–150.
Kleiner, Y. and Rajani, B. B., and (2007). “Static and dynamic effects in prioritizing individual water mains for renewal.” Proc., Int. Conf. on Water Management Challenges in Global Change (CCWI2007 and SUWM2007), B. Ulaniki, ed., Taylor and Francis, Bristol, Pa., 61–68.
Lansey, K. E., Basnet, C., Mays, L. W., and Woodburn, J. (1992). “Optimal maintenance scheduling for water distribution systems.” Civ. Eng. Syst., 9(3), 211–226.
Lawson, C. L., and Hanson, R. J. (1974). Solving least squares problems, Prentice-Hall, Englewood Cliffs, N.J., 161.
Li, D., and Haimes, Y. Y. (1992). “Optimal maintenance-related decision making for deteriorating water distribution systems—2. Multi-level decomposition approach.” Water Resour. Res., 28(4), 1063–1070.
Loganathan, G. V., Park, S., and Sherali, H. D. (2002). “Threshold break rate for pipeline replacement in water distribution systems.” J. Water Resour. Plann. Manage., 128(4), 271–279.
Male, J. W., Walski, T. M., and Slutsky, A. H. (1990). “Analyzing water main replacement policies.” J. Water Resour. Plann. Manage., 116(3), 362–374.
McKay, M. D., Conover, W. J., and Beckman, R. J. (1979). “A comparison of three methods for selecting values of input variables in the analysis of output from a computer code.” Technometrics, 21(2), 239–245.
Pareto, V. (1896). Cours d'economie politique, Université de Lausanne, Lausanne, Switzerland.
Quimpo, R. G., and Shamsi, U. M. (1991). “Reliability based distribution system maintenance.” J. Water Resour. Plann. Manage., 117(3), 321–339.
Ramos, W. L. (1985). “Benefit/cost analysis procedure for determining water main replacement.” Proc., of AWWA Symp., American Water Works Association, Denver, Colo., 125–133.
Savic, D. A. (2002). “Single-objective vs. multiobjective optimisation for integrated decision support integrated assessment and decision support.” Proc., First Biennial Meeting of the Int. Environmental Modeling and Software Society, Vol. 1, A. E. Rizzoli and A. J. Jakeman, eds., Univ. of Lugano, Lugano, Switzerland, 7–12.
Schneiter, C. R., Haimes, Y. Y., Li, D., and Lambert, J. H. (1996). “Capacity reliability of water distribution networks and optimum rehabilitation decision making.” Water Resour. Res., 32(7), 2271–2278.
Shamir, U., and Howard, C. D. D. (1979). “An analytic approach to scheduling pipe replacement.” J. Am. Water Works Assoc., 117(5), 248–258.
Skipworth, P., Engelhardt, M., Cashman, A., Savic, D. A., Saul, A. J., and Walters, G. A. (2002). Whole life costing for water distribution network management, Thomas Telford, London.
Walski, T. M. (1985). “Cleaning and lining versus parallel mains.” J. Water Resour. Plann. Manage., 111(1), 43–53.
Walski, T. M. (1987). “Water supply system rehabilitation.” Task committee on water supply system rehabilitation, ASCE, New York.
Walski, T. M., and Pelliccia, A. (1982). “Economic analysis of water main breaks.” J. Am. Water Works Assoc., 74(3), 140–147.
Watson, T. G. (2005). “A hierarchical Bayesian model and simulation software for water pipe networks.” Ph.D. thesis, Univ. of Auckland, Auckland, New Zeland.
Zitzler, E., and Thiele, L. (1998). “Multiobjective optimization using evolutionary algorithms—a comparative case study.” Proc., Fifth Int. Conf. on Parallel Problem Solving from Nature (PPSN-V), A. E. Eiben, T. Bäck, M. Schoenauer, and H. -P. Schwefel, eds., Springer, Berlin, Germany, 292–301.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 135 • Issue 6 • November 2009
Pages: 484 - 492
Copyright
© 2009 ASCE.
History
Received: Oct 19, 2007
Accepted: Apr 7, 2009
Published online: Oct 15, 2009
Published in print: Nov 2009
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.