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Resilience-Driven Management of Water Distribution Networks


Resilience-Driven Management of Water Distribution Networks

Assad, Ahmed ORCID: https://orcid.org/0000-0002-7363-6646 (2020) Resilience-Driven Management of Water Distribution Networks. PhD thesis, Concordia University.

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Water distribution networks (WDNs) are critical infrastructure systems that secure needed supply of potable water to the public. Efficient management of WDNs has always been a primary concern for decision-makers, particularly in events of natural disasters, deliberate attacks, human-made accidents and/or sudden failures. Aging and deterioration of WDNs further exacerbate their vulnerability and likelihood of service disruption. Previous hazards reveal that classical risk-based approaches are not sufficient to prevent disruptions of WDNs. As a result, the concept of resilient WDNs has emerged to cope up with inevitable disruptions that are becoming more frequent.
The objective of this research is to develop a holistic resilience-based management model for WDNs. In this context, WDNs is sought to be strong enough to withstand unforeseen disruptions with a minimum performance impact and to recover rapidly after a service interruption. Firstly, a multi-attribute metric is developed for assessing resilience of WDNs based on robustness and redundancy. Attributes from graph theory are employed to quantify the network redundancy. Robustness is measured by integrating the reliability and criticality of pipe segments of the network. Multi-attribute utility theory and Fuzzy analytical network process are exploited to estimate the criticality of water segments based on a set of economic, social, and environmental factors. Survival analysis and maximum likelihood estimate are employed to dynamically determine reliability of pipe segments. Censored inter-failure time data are leveraged to model the deterioration behavior of homogenous cohorts of pipe. The developed metric was used to measure the resilience of a real-life WDN in the City of London, Ontario. The results obtained showed an average of 5% variation when compared to previously developed flow-based and topology-based metrics.
In the second step, rapidity and resourcefulness qualities are considered to develop a resilience-based restoration model. A failure scenario causing multiple simultaneous breaks across the network is simulated to investigate the recovery process. A stochastic multi-objective optimization model that maximizes resilience while minimizing the total time and cost of the recovery process is then formulated. This model accounts for different restoration methods, relocation time and cost of restoration crews, and uncertainties in recovery estimates. The optimum restoration plan encompasses a sequence of failed segments restorations along with the restoration method. This plan achieved 4% cost saving, 48% duration reduction, and 4% resilience improvement when compared to current planning practices.
The last step involves developing a multi-objective resilience enhancement model so that WDNs can be better prepared for future disruptions. The aim is to maximize resilience of WDNs while minimizing the life cycle cost and carbon emissions of enhancement actions. Optimum enhancement interventions are firstly determined and clustered into work packages before an optimized schedule is generated considering various operational and managerial factors. Applied to a section of an actual WDN of 34 km in a length and average age of 40 years, resilience was increased by 20% with CAD 1.65 million of current investment. The study of that network indicates that a cost-saving of 32% could be attained when adopting the developed model over ongoing portfolio management practices.
The novel resilience-driven management model introduced in this research is expected to assist decision-makers better assess and enhance resilience of WDNs and improve restoration planning. The developed model can assist city mangers in allocation and utilization of resources more effectively in development of optimized plans for resilient and sustainable WDNs.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (PhD)
Authors:Assad, Ahmed
Institution:Concordia University
Degree Name:Ph. D.
Program:Civil Engineering
Date:9 September 2020
Thesis Supervisor(s):Moselhi, Osama and Zayed, Tarek
Keywords:Resilience, Water distribution networks, Absorptive capacity, Restoration scheduling, Multi-objective optimization
ID Code:987592
Deposited By: Ahmed Assad
Deposited On:29 Jun 2021 20:48
Last Modified:31 Dec 2022 01:00


Abdullah, L., Chan, W., & Afshari, A. (2019). Application of PROMETHEE method for green supplier selection: A comparative result based on preference functions. Journal of Industrial Engineering International, 15(2), 271-285.
Adams, T. M., Bekkem, K. R., & Toledo-Duran, E. J. (2012). Freight resilience measures. Journal of Transportation Engineering, 138(11), 1403-1409.
Akyene, T. (2012). Cell phone evaluation base on entropy and TOPSIS. Interdisciplinary Journal of Research in Business, 1(12), 9-15.
Alan Atalah. (2009). Pipe bursting (2nd Ed.). Irving, TX: Plastics Pipe Institute. Retrieved from http://www.knovel.com/web/portal/browse/display?_EXT_KNOVEL_DISPLAY_bookid=5198
Almoghathawi, Y., Barker, K., & Albert, L. A. (2019). Resilience-driven restoration model for interdependent infrastructure networks. Reliability Engineering & System Safety, 185, 12-23.
Archetti, F., Candelieri, A., & Soldi, D. (2015). Network analysis for resilience evaluation in water distribution networks. Environmental Engineering and Management Journal, 14(6), 1261-1270.
ASCE. (2017). 2017 infrastructure report card. USA: American Society of Civil Engineers. Retrieved from https://www.infrastructurereportcard.org/
Assad, A., Moselhi, O., & Zayed, T. (2019). A new metric for assessing resilience of water distribution networks. Water, 11(8), 1701.
Assad, A., Moselhi, O., & Zayed, T. (2020). Resilience-driven multiobjective restoration planning for water distribution networks. Journal of Performance of Constructed Facilities, 34(4), 04020072.
Ayyub, B. M. (2014). Systems resilience for multihazard environments: Definition, metrics, and valuation for decision making. Risk Analysis, 34(2), 340-355.
Bałut, A., Brodziak, R., Bylka, J., & Zakrzewski, P. (2019). Ranking approach to scheduling repairs of a water distribution system for the post-disaster response and restoration service. Water, 11(8), 1591.
Baños, R., Reca, J., Martínez, J., Gil, C., & Márquez, A. L. (2011). Resilience indexes for water distribution network design: A performance analysis under demand uncertainty. Water Resources Management, 25(10), 2351-2366.
Barker, K., Ramirez-Marquez, J. E., & Rocco, C. M. (2013). Resilience-based network component importance measures. Reliability Engineering & System Safety, 117, 89-97.
Baroud, H., Barker, K., & Ramirez-Marquez, J. E. (2014). Importance measures for inland waterway network resilience. Transportation Research Part E: Logistics and Transportation Review, 62, 55-67.
Basu, S. (2012). Tabu search implementation on traveling salesman problem and its variations: A literature survey. American Journal of Operations Research, 2(2), 163.
Beale, D. J., Marlow, D. R., & Cook, S. (2013). Estimating the cost and carbon impact of a long term water main rehabilitation strategy. Water Resources Management, 27(11), 3899-3910.
Bentley Systems Incorporated. WaterGEMS v8Users Manual 2006, Haestad Methods Solution Center, Watertown, NY, USA.
Bocchini, P., Frangopol, D. M., Ummenhofer, T., & Zinke, T. (2013). Resilience and sustainability of civil infrastructure: Toward a unified approach. Journal of Infrastructure Systems, 20(2), 04014004.
Brandão, J. (2009). A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem. European Journal of Operational Research, 195(3), 716-728.
Brans, J., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research, 24(2), 228-238.
Brashear, J. P., & Jones, J. W. (2008). Risk analysis and management for critical asset protection (RAMCAP plus). Wiley Handbook of Science and Technology for Homeland Security,
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O’Rourke, T. D., Reinhorn, A. M. . . . Von Winterfeldt, D. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 19(4), 733-752.
Chang, S. E., & Shinozuka, M. (2004). Measuring improvements in the disaster resilience of communities. Earthquake Spectra, 20(3), 739-755.
Cheng, C., Yang, K., & Hwang, C. (1999). Evaluating attack helicopters by AHP based on linguistic variable weight. European Journal of Operational Research, 116(2), 423-435.
Choi, Y. H., & Kim, J. H. (2019). Development of multi-objective optimal redundant design approach for multiple pipe failure in water distribution system. Water, 11(3), 553.
Cimellaro, G. P., Tinebra, A., Renschler, C., & Fragiadakis, M. (2015). New resilience index for urban water distribution networks. Journal of Structural Engineering, 142(8), C4015014.
Cimellaro, G. P., Tinebra, A., Renschler, C., & Fragiadakis, M. (2015). New resilience index for urban water distribution networks. Journal of Structural Engineering, 142(8), C4015014.
Cimorelli, L., Morlando, F., Cozzolino, L., D’Aniello, A., & Pianese, D. (2018). Comparison among resilience and entropy index in the optimal rehabilitation of water distribution networks under limited-budgets Water Resources Management, 32(12), 3997-4011.
CIRC. (2019). Monitoring the state of Canada’s core public infrastructure: The Canadian infrastructure report card 2019. Canada: The Canadian Infrastructure Report Card.
Collins, P. A., & Baggett, R. K. (2009). Homeland security and critical infrastructure protection. Westport, Conn: Praeger Security International.
Creaco, E., Franchini, M., & Todini, E. (2016). Generalized resilience and failure indices for use with pressure-driven modeling and leakage. Journal of Water Resources Planning and Management, 142(8), 04016019.
Cromwell, J. E. (2002). Costs of infrastructure failure. American Water Works Association.
Cutter, S. L., Ahearn, J. A., Amadei, B., Crawford, P., Eide, E. A., Galloway, G. E., . . . Schoch-Spana, M. (2013). Disaster resilience: A national imperative. Environment: Science and Policy for Sustainable Development, 55(2), 25-29.
Cutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., & Webb, J. (2008). A place-based model for understanding community resilience to natural disasters. Global Environmental Change, 18(4), 598-606.
Da Conceicao Cunha, M., & Ribeiro, L. (2004). Tabu search algorithms for water network optimization. European Journal of Operational Research, 157(3), 746-758.
Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, (2), 224-227.
Dessavre, D. G., Ramirez-Marquez, J. E., & Barker, K. (2016). Multidimensional approach to complex system resilience analysis. Reliability Engineering & System Safety, 149, 34-43.
Di Nardo, A., Di Natale, M., Giudicianni, C., Greco, R., & Santonastaso, G. F. (2018). Complex network and fractal theory for the assessment of water distribution network resilience to pipe failures. Water Science and Technology: Water Supply, 18(3), 767-777.
Dorigo, M., Birattari, M., & Stutzle, T. (2006). Ant colony optimization. IEEE Computational Intelligence Magazine, 1(4), 28-39.
Dorigo, M., & Gambardella, L. M. (1997). Ant colonies for the travelling salesman problem. Biosystems, 43(2), 73-81.
Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 26(1), 29-41.
El Chanati, H. (2014). Performance assessment of water network infrastructure. Doctoral dissertation, Concordia University, Montreal, QC, Canada.
El-Abbasy, M. S., El Chanati, H., Mosleh, F., Senouci, A., Zayed, T., & Al-Derham, H. (2016). Integrated performance assessment model for water distribution networks. Structure and Infrastructure Engineering, 12(11), 1505-20. doi:10.1080/15732479.2016.1144620
Elbeltagi, E., Hegazy, T., & Grierson, D. (2005). Comparison among five evolutionary-based optimization algorithms. Advanced Engineering Informatics, 19(1), 43-53.
El-Ghandour, H. A., & Elbeltagi, E. (2017). Comparison of five evolutionary algorithms for optimization of water distribution networks. Journal of Computing in Civil Engineering, 32(1), 04017066. Doi: 10.1061/ (ASCE) CP.1943-5487.0000717
ESRI (2011). "ArcGIS Desktop: Release 10". Redlands, CA: Environmental Systems Research Institute, 437, 438.
Etaati, L., Sadi-Nezhad, S., & Moghadam-Abyaneh, P. M. (2011). Fuzzy analytical network process: An overview on methods. American Journal of Scientific Research, 41, 101-114.
Exler, O., & Schittkowski, K. (2007). A trust region SQP algorithm for mixed-integer nonlinear programming. Optimization Letters, 1(3), 269-280.
Farahmandfar, Z., & Piratla, K. R. (2017a). Comparative evaluation of topological and flow-based seismic resilience metrics for rehabilitation of water pipeline systems. Journal of Pipeline Systems Engineering and Practice, 9(1), 04017027.
Farahmandfar, Z., & Piratla, K. R. (2017b). Resilience-based water main rehabilitation planning in a multi-hazard context. Journal of Water Supply: Research and Technology-Aqua, 66(8), 651-664.
Farahmandfar, Z., Piratla, K. R., & Andrus, R. D. (2016). Resilience evaluation of water supply networks against seismic hazards. Journal of Pipeline Systems Engineering and Practice, 8(1), 04016014.
Fiksel J, Goodman I, Hecht A. (2014). Resilience: Navigating a sustainable future. Solutions, 5(5), 38-47.
Fisher, R. E., Bassett, G. W., Buehring, W. A., Collins, M. J., Dickinson, D. C., Eaton, L. K., ... & Millier, D. J. (2010). Constructing a resilience index for the enhanced critical infrastructure protection program (No. ANL/DIS-10-9). Argonne National Lab. (ANL), Argonne, IL (United States). Decision and Information Sciences.
Gay Alanis, L. F. (2013). Development of a resilience assessment methodology for networked infrastructure systems using stochastic simulation, with application to water distribution systems. Doctoral dissertation, Virginia Tech, Virginia, USA.
Gheisi, A., & Naser, G. (2014). A surrogate measure for multi-component failure based reliability analysis of water distribution systems. Procedia Engineering, 89, 333-338.
Glover, F. (1997). Tabu search and adaptive memory programming—advances, applications and challenges. Interfaces in computer science and operations research (pp. 1-75). Springer, Boston, MA, USA.
He, X., & Yuan, Y. (2019). A framework of identifying critical water distribution pipelines from recovery resilience. Water Resources Management, 33(11), 3691-3706.
Henry, D., & Ramirez-Marquez, J. E. (2012). Generic metrics and quantitative approaches for system resilience as a function of time. Reliability Engineering & System Safety, 99, 114-122.
Herrera, M., Abraham, E., & Stoianov, I. (2016). A graph-theoretic framework for assessing the resilience of sectorised water distribution networks. Water Resources Management, 30(5), 1685-1699.
Holland, J. H. (1975). Adaptation in natural and artificial systems. An introductory analysis with application to biology, control, and artificial intelligence. Ann Arbor, MI: University of Michigan Press. 439-444.
Hosseini, S., Barker, K., & Ramirez-Marquez, J. E. (2016). A review of definitions and measures of system resilience. Reliability Engineering & System Safety, 145, 47-61. doi:10.1016/j.ress.2015.08.006
InfraGuide. (2004). Managing infrastructure assets. Decision making and investment planning (DMIP) best practice.
Işıklar, G., & Büyüközkan, G. (2007). Using a multi-criteria decision making approach to evaluate mobile phone alternatives. Computer Standards & Interfaces, 29(2), 265-274.
Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651-666.
Jardine, A. K., & Tsang, A. H. (2013). Maintenance, replacement, and reliability: Theory and applications. Florida: Taylor and Francis Group.
Jayaram, N., & Srinivasan, K. (2008). Performance‐based optimal design and rehabilitation of water distribution networks using life cycle costing. Water Resources Research, 44(1)
Kiriş, Ş. (2013). Multi-criteria inventory classification by using a fuzzy analytic network process (ANP) approach. Informatica, 24(2), 199-217.
Kleinbaum, D. G., & Klein, M. (2010). Survival analysis. New York, USA. Springer.
Klise, K. A., Murray, R., & Walker, L. T. N. (2015). Systems measures of water distribution system resilience (No. SAND2015-20746R). Sandia National Lab. (SNL-NM), Albuquerque, NM (United States).
Laucelli, D., & Giustolisi, O. (2015). Vulnerability assessment of water distribution networks under seismic actions. Journal of Water Resources Planning and Management, 141(6), 04014082.
Law, A. M., Kelton, W. D., & Kelton, W. D. (2000). Simulation modeling and analysis (Vol. 3). New York: McGraw-Hill.
Lawler, E. L., Lenstra, J. K., Rinnooy Kan, A. H., & Shmoys, D. B. (1985). The traveling salesman problem; a guided tour of combinatorial optimization John Wiley & sons.
Lee, M. C. (2010). The analytic hierarchy and the network process in multicriteria decision making: Performance evaluation and selecting key performance indicators based on ANP model. Convergence and Hybrid Information Technologies, 426.
Liu, H., Savić, D. A., Kapelan, Z., Creaco, E., & Yuan, Y. (2017). Reliability surrogate measures for water distribution system design: Comparative analysis. Journal of Water Resources Planning and Management, 143(2), 04016072.
Liu, W., Song, Z., Ouyang, M., & Li, J. (2020). Recovery-based seismic resilience enhancement strategies of water distribution networks. Reliability Engineering & System Safety. 107088.
Luna, R., Balakrishnan, N., & Dagli, C. H. (2011). Postearthquake recovery of a water distribution system: Discrete event simulation using colored petri nets. Journal of Infrastructure Systems, 17(1), 25-34.
Mahmoud, H. A., Kapelan, Z., & Savić, D. (2018). Real-time operational response methodology for reducing failure impacts in water distribution systems. Journal of Water Resources Planning and Management, 144(7), 04018029.
Mareschal, B., & De Smet, Y. (2009). Visual Promethee: Developments of the PROMTHEE & GAIA multicriteria decision aid methods. In the Proceedings of the IEEE 2009 International Conference on Industrial Engineering and Engineering Management (pp 1646-1649), Hong Kong.
Maier, H. R., Simpson, A. R., Zecchin, A. C., Foong, W. K., Phang, K. Y., Seah, H. Y., & Tan, C. L. (2003). Ant colony optimization for design of water distribution systems. Journal of Water Resources Planning and Management, 129(3), 200-209.
Meirelles, G., Brentan, B., Izquierdo, J., Ramos, H., & Luvizotto, E. (2018). Trunk network rehabilitation for resilience improvement and energy recovery in water distribution networks. Water, 10(6), 693.
Meng, F., Fu, G., Farmani, R., Sweetapple, C., & Butler, D. (2018). Topological attributes of network resilience: A study in water distribution systems. Water Research, 143, 376-386.
Mierswa, I., Wurst, M., Klinkenberg, R., Scholz, M., & Euler, T. (2006). Yale: Rapid prototyping for complex data mining tasks. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 935-940).
Mohammed, A. U. (2016). Integrated reliability assessment of water distribution networks. Doctoral dissertation, Concordia University, Montreal, QC, Canada.
Moursi. (2016). Priority assessment model for water distribution networks. Doctoral dissertation, Concordia University, Montreal, QC, Canada.
Murthy, D. P., Rausand, M., & Østerås, T. (2008). Product reliability: Specification and performance Springer Science & Business Media.
Nebro, A. J., Durillo, J. J., & Coello, C. A. C. (2013). (2013). Analysis of leader selection strategies in a multi-objective particle swarm optimizer. Paper presented at the 2013 IEEE Congress on Evolutionary Computation, 3153-3160.
Nicholson, C. D., Barker, K., & Ramirez-Marquez, J. E. (2015). Vulnerability analysis for resilience-based network preparedness. Reliab Eng Syst Saf, (145), 62–73.
Nunoo, C. N. (2001). Optimization of pavement maintenance and rehabilitation programming using shuffled complex evolution algorithm. Florida International University.
O’Sullivan D (2010). Reduce your carbon footprint using trenchless. No Dig Show 2010, Chicago, Illinois, USA, North American Society for Trenchless Technology.
Ouyang, M., Duenas-Osorio, L., & Min, X. (2012). A three-stage resilience analysis framework for urban infrastructure systems. Structural Safety, 36, 23-31.
Pant, R., Barker, K., Ramirez-Marquez, J. E., & Rocco, C. M. (2014). Stochastic measures of resilience and their application to container terminals. Computers & Industrial Engineering, 70, 183-194.
Pisinger, D., & Toth, P. (1998). Knapsack problems. Handbook of combinatorial optimization (pp. 299-428). Boston, MA, USA: Springer.
Polat, G. (2016). Subcontractor selection using the integration of the AHP and PROMETHEE methods. Journal of Civil Engineering and Management, 22(8), 1042-1054.
Prasad, T. D., & Park, N. (2004). Multiobjective genetic algorithms for design of water distribution networks. Journal of Water Resources Planning and Management, 130(1), 73-82.
Riquelme, N., Von Lücken, C., & Baran, B. (2015, October). Performance metrics in multi-objective optimization. In 2015 Latin American Computing Conference (CLEI) (pp. 1-11). IEEE.
Rose, A. (2007). Economic resilience to natural and man-made disasters: Multidisciplinary origins and contextual dimensions. Environmental Hazards, 7(4), 383-398.
Saaty, T. L. (2007). The analytic hierarchy and analytic network measurement processes: Applications to decisions under risk. European Journal of Pure and Applied Mathematics, 1(1), 122-196.
Sahani, R., & Bhuyan, P. K. (2017). Pedestrian level of service criteria for urban off-street facilities in mid-sized cities. Transport, 32(2), 221-232.
Sahebjamnia, N., Torabi, S. A., & Mansouri, S. A. (2015). Integrated business continuity and disaster recovery planning: Towards organizational resilience. European Journal of Operational Research, 242(1), 261-273.
Salman, A. (2011). Reliability-based management of water distribution networks. Doctoral dissertation, Concordia University, Montreal, QC, Canada.
Sawant, K. B. (2015). Efficient determination of clusters in K-mean algorithm using neighborhood distance. The International Journal of Emerging Engineering Research and Technology, 3(1), 22-27.
Schlüter, M., Egea, J. A., & Banga, J. R. (2009). Extended ant colony optimization for non-convex mixed integer nonlinear programming. Computers & Operations Research, 36(7), 2217-2229.
Schlüter, M., Gerdts, M., & Rückmann, J. (2012). A numerical study of MIDACO on 100 MINLP benchmarks. Optimization, 61(7), 873-900.
Shahata, K. F. (2013). Decision-support framework for integrated asset management of major municipal infrastructure. Doctoral dissertation, Concordia University, Montreal, QC, Canada.
Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(3), 379-423.
Shuang, Q., Liu, H. J., & Porse, E. (2019). Review of the quantitative resilience methods in water distribution networks. Water, 11(6), 1189.
Simicevic, J., & Sterling, R. L. (2001). Guidelines for pipe bursting. US Army Corps of Engineers, Vicksburg, Miss. TTC technical report, (2001.02).
Soldi, D., Candelieri, A., & Archetti, F. (2015). Resilience and vulnerability in urban water distribution networks through network theory and hydraulic simulation. Procedia Engineering, 119, 1259-1268.
Srichetta, P., & Thurachon, W. (2012). Applying fuzzy analytic hierarchy process to evaluate and select product of notebook computers. International Journal of Modeling and Optimization, 2(2), 168.
Suribabu, C. R. (2017). Resilience-based optimal design of water distribution network. Applied Water Science, 7(7), 4055-4066.
Suribabu, C. R., Prashanth, K., Vignesh Kumar, S., & Ganesh, N. S. (2016). Resilience enhancement methods for water distribution networks. Jordan Journal of Civil Engineering, 10(2).
Tabesh, M., Yekta, A. A., & Burrows, R. (2009). An integrated model to evaluate losses in water distribution systems. Water Resources Management, 23(3), 477-492.
Tierney, K., & Bruneau, M. (2007). Conceptualizing and measuring resilience: A key to disaster loss reduction. TR News, (250)
Todini, E. (2000). Looped water distribution networks design using a resilience index based heuristic approach. Urban Water, 2(2), 115-122.
Torres, J. M., Duenas-Osorio, L., Li, Q., & Yazdani, A. (2017). Exploring topological effects on water distribution system performance using graph theory and statistical models. Journal of Water Resources Planning and Management, 143(1), 04016068.
Vanier, D. J., & Rahman, S. (2004). A primer on municipal infrastructure asset management. University of British Columbia, Vancouver: NRC.
Verma, A. K., Ajit, S., & Karanki, D. R. (2010). Reliability and safety engineering (Vol. 43, pp. 373-392). London: Springer.
Vugrin, E. D., Warren, D. E., & Ehlen, M. A. (2011). A resilience assessment framework for infrastructure and economic systems: Quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane. Process Safety Progress, 30(3), 280-290.
Wang, S., Hong, L., & Chen, X. (2012). Vulnerability analysis of interdependent infrastructure systems: A methodological framework. Physica A: Statistical Mechanics and its Applications, 391(11), 3323-3335.
Weaver, T., & Woodcock, M. E. (2014) Pipe bursting water lines with confidence. North American Society for Trenchless Technology (NASTT) NASTT’s 2014 no-Dig Show, Orlando, Florida, USA.
Wei, J. Y., Sun, A. F., & Wang, C. H. (2010, January). The application of fuzzy-ANP in the selection of supplier in supply chain management. In 2010 International Conference on Logistics Systems and Intelligent Management (ICLSIM) (Vol. 3, pp. 1357-1360). IEEE.
Yazdani, A., Otoo, R. A., & Jeffrey, P. (2011). Resilience enhancing expansion strategies for water distribution systems: A network theory approach. Environmental Modelling & Software, 26(12), 1574-1582.
Yazdani, A., & Jeffrey, P. (2011). Complex network analysis of water distribution systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 21(1), 016111-10.
Yazdani, A., & Jeffrey, P. (2012). Water distribution system vulnerability analysis using weighted and directed network models. Water Resources Research, 48(6)
Yazdekhasti, S., Piratla, K. R., Khan, A., & Atamturktur, S. Analysis of factors influencing the selection of water main rehabilitation methods. Paper presented at the North American Society for Trenchless Technology (NASTT).
Yoo, D. G., Kang, D., Jun, H., & Kim, J. H. (2014). Rehabilitation priority determination of water pipes based on hydraulic importance. Water, 6(12), 3864-3887.
Zadeh, L. A. (1965). Information and control. Fuzzy Sets, 8(3), 338-353.
Zarghami, S. A., Gunawan, I., & Schultmann, F. (2018). Integrating entropy theory and cospanning tree technique for redundancy analysis of water distribution networks. Reliability Engineering & System Safety, 176, 102-112.
Zhao, X., Cai, H., Chen, Z., Gong, H., & Feng, Q. (2016). Assessing urban lifeline systems immediately after seismic disaster based on emergency resilience. Structure and Infrastructure Engineering, 12(12), 1634-1649.
Zhao, X., Chen, Z., & Gong, H. (2015). Effects comparison of different resilience enhancing strategies for municipal water distribution network: A multidimensional approach. Mathematical Problems in Engineering, 2015.
Zhuang, B., Lansey, K., & Kang, D. (2013). Resilience/availability analysis of municipal water distribution system incorporating adaptive pump operation. Journal of Hydraulic Engineering, 139(5), 527-537.
Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C. M., & Da Fonseca, V. G. (2003). Performance assessment of multiobjective optimizers: An analysis and review. IEEE Transactions on Evolutionary Computation, 7(2), 117-132.
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