Framework for Computing a Performance Index for Urban Infrastructure Systems Using a Fuzzy Set Approach
Publication: Journal of Infrastructure Systems
Volume 17, Issue 4
Abstract
This paper presents a framework for characterizing, analyzing, and computing the performance of urban infrastructure systems. The framework is based on a systems approach and consists of performance indicators classified into three hierarchical levels: indicators, dimensions, and categories. A fuzzy synthetic evaluation technique has been developed to synthesize performance indicators into an index that ranges between 0 and 100. The performance of an individual infrastructure system, in the form of an index, is generated by aggregating the performance indicators in the first three hierarchical levels. The overall performance of the urban infrastructure systems is then obtained by combining the indexes of individual infrastructure systems. The relative importance of the performance indicators during the synthesis process is determined using the analytic hierarchy process technique. The framework demonstrates and measures the performance of the civil infrastructure systems in Kathmandu, Nepal. This framework can be applied to performance analysis of any infrastructure system in an urban area. It enables decision makers to identify the weak and strong components of urban infrastructure systems and to formulate appropriate strategies for infrastructure planning on the basis of performance and investment costs.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writers would like to acknowledge the financial support of the Delft Cluster, Delft, and SWITCH project UNESCO-IHE, Delft, The Netherlands, that enabled this research to be conducted. The writers acknowledge the constructive critiques and contribution of the three anonymous reviewers and, most important, the coeditor of this journal. The writers are also indebted to Shreedhar Maskey for his early contribution to some parts of this paper.
References
Abrishamchi, A., Ebrahimian, A., Tajrishi, M., and Mariño, M. A. (2005). “Case study: Application of multi-criteria decision making to urban water supply.” J. Water Resour. Plann. Manage., 131(4), 326–335.
Alegre, H., et al. (2006). Performance indicators for water supply services, IWA Publishing, London.
American Society of Civil Engineers (ASCE). (2005). “The New Orleans hurricane protection system: What went wrong and why.” Rep. by the American Society of Civil Engineers Hurricane Katrina External Review Panel.
Ananda, J., and Herath, G. (2009). “A critical review of multi-criteria decision making methods with special reference in forest management and planning.” Ecol. Econ., 68(10), 2535–2548.
Ashley, R., Blackwood, D., Butler, D., and Jowitt, P. (2004). Sustainable water services—A procedural guide, IWA Publishing, London.
Bell, M. L., Hobbs, B. F., and Ellis, H. (2003). “The use of multi-criteria decision-making methods in the integrated assessment of climate change: Implications for IA practitioners.” Socio-Econ. Plann. Sci., 37, 289–316.
Belton, V., and Stewart, T. (2002). Multiple criteria decision analysis: An integrated approach, Kluwer Academic Publications, Boston.
Chang, N.-B., Chen, H. W., and Ning, S. K. (2001). “Identification of river water quality using the fuzzy synthetic evaluation approach.” J. Environ. Manage., 63, 293–305.
Chen, G., and Pham, T. T. (2001). Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems, CRC Press, Boca Raton, FL.
Chiu, S. L. (1994). “Fuzzy model identification based on cluster estimation.” J. Intell. Fuzzy Syst., 2, 267–278.
Dasgupta, S., and Tam, E. K. L. (2005). “Indicators and framework for assessing sustainable infrastructure.” Can. J. Civ. Eng., 32, 30–44.
Dubois, D., and Prade, H. (1980). Fuzzy sets and system—Theory and applications, Academic Press, San Diego.
Fisher, B. (2003). “Fuzzy environmental decision-making: Applications to air pollution.” Atmos. Environ., 37, 1865–1877.
Flintsch, G. W., and Chen, C. (2004). “Soft computing applications in infrastructure management.” J. Infrastruct. Syst., 10(4), 157–166.
Geerse, J. M. U., and Lobbrecht, A. H. (2002). “Assessing the performance of urban drainage systems ‘general approach’ applied to the city of Rotterdam.” Urban Water, 4, 199–209.
Gilovich, T., Griffin, D., and Kahneman, D. (2002). Heuristics and biases, Cambridge University Press, New York.
Guitouni, A., and Martel, J.-M. (1998). “Tentative guidelines to help choosing an appropriate MCDA method.” Eur. J. Oper. Res., 109(2), 501–521.
Haiyan, W. (2002). “Assessment and prediction of overall environmental quality of Zhuzhou city, Hunan province, China.” J. Environ. Manage., 66(2), 329–340.
Hämäläinen, R. P., and Alaja, S. (2008). “The threat of weighting biases in environmental decision analysis.” Ecol. Econ., 68(1–2), 556–569.
Hansman, R. J., Magee, C., Neufville, R. de., Robins, R., and Roos, D. (2006). “Research agenda for an integrated approach to infrastructure planning, design and management.” Int. J. Crit. Infrastruct., 2(2/3), 146–159.
Jacobi, S. K., and Hobbs, B. F. (2007). “Quantifying and mitigating the splitting bias and other value tree-induced weighting biases.” Decis. Anal., 4(4), 194–210.
Jang, J.-S. R. (1993). “ANFIS: Adaptive-network-based fuzzy inference system.” IEEE Trans. Syst. Man Cybern., 23(3), 665–685.
Jasch, C. (2000). “Environmental performance evaluation and indicators.” J. Cleaner Prod., 8(1), 79–88.
Karwowski, W., and Mital, A. (1986). “Potential applications of fuzzy sets in industrial safety engineering.” Fuzzy Sets Syst., 19(2), 105–120.
Kaufmann, A., and Gupta, M. M. (1991). Introduction to fuzzy arithmetic: Theory and applications, Van Nostrand Reinhold, New York.
Keating, C., et al. (2003). “System of systems engineering.” Eng. Manage. J., 15(3), 36–45.
Keeney, R. L. (2002). “Common mistakes in making value trade-offs.” Oper. Res., 50(6), 935–945.
Klir, G., and Yuan, B. (1995). Fuzzy sets and fuzzy logic theory and applications, Prentice-Hall, Englewood Cliffs, NJ.
Kolsky, P., and Butler, D. (2002). “Performance indicators for urban storm drainage in developing countries.” Urban Water, 4(2), 137–144.
Kovats, S., and Akhtar, R. (2008). “Climate, climate change and human health in Asian cities.” Environ. Urban., 20(1), 165–175.
Lu, R. S., and Lo, S. L. (2002). “Diagnosing reservoir water quality using self-organizing maps and fuzzy theory.” Water Res., 36(9), 2265–2274.
Lu, R. S., Lo, S. L., and Hu, J. Y. (1999). “Analysis of reservoir water quality using fuzzy synthetic evaluation.” Stoch. Environ. Res. Risk Assess., 13(5), 327–336.
Maskey, S., Guinot, V., and Price, R. K. (2004). “Treatment of precipitation uncertainly in rainfall-runoff modeling: A fuzzy set approach.” Adv. Water Resour., 27(9), 889–898.
Matos, R., Cardoso, A., Ashley, R., Durate, P., Molinari, A., and Schulz, A. (2003). Performance indicators for wastewater services, IWA Publishing, London.
Miller, G. (1956). “The magical number seven, plus or minus two: Some limits on our capacity for processing information.” Psychol. Rev., 63(2), 81–97.
Molden, D. J., and Gates, T. K. (1990). “Performance measures for evaluation of irrigation water delivery systems.” J. Irrig. Drain. Eng., 116(6), 804–823.
National Research Centre. (1996). Measuring and improving infrastructure performance. National Research Centre (NRC), National Academies Press, Washington, DC.
Pedrycz, W. (1989). Fuzzy control and fuzzy systems, Wiley, New York.
Peerenboom, J. P., and Fisher, R. E. (2007). “Analyzing cross-sector interdependencies.” Proc., Hawaii International Conf. on System Sciences, Waikoloa, Big Island, HI.
Pohekar, S. D., and Ramachandran, M. (2004). “Application of multi-criteria decision making to sustainable energy planning: A review.” Renew. Sustain. Energ. Rev., 8(4), 365–381.
Prato, T., and Herath, G. (2007). “Multiple-criteria decision analysis for integrated catchment management.” Ecol. Econ., 63(2–3), 627–632.
Ranjani, B., Kleiner, Y., and Sadiq, R. (2006). “Translation of pipe inspection results into condition rating using the fuzzy synthetic evaluation technique.” J. Water Supply: Res. Technol.—AQUA, 55(1), 11–24.
Roy, B. (2005). “Paradigms and challenges.” An overview of MCDA techniques today, multiple criteria decision analysis: State of the art surveys, J. Figueira, S. Greco, and M. Ehrgott, eds., Springer Science, Boston.
Saaty, T. L. (1988). Multi-criteria decision-making: The analytic hierarchy process, University of Pittsburgh, Pittsburgh, PA.
Sadiqa, R., and Rodriguez, M. J. (2004). “Fuzzy synthetic evaluation of disinfection by-products: A risk-based indexing system.” J. Environ. Manage., 73(1), 1–13.
Severn Trent Water. (2007). “Gloucestershire 2007 the impact of the July floods on the water infrastructure and customer service.” Final report.
Silvert, W. (2000). “Fuzzy indices of environmental conditions.” Ecol. Model., 130(1–3), 111–119.
Talvitie, A. (1999). “Performance indicators for the road sector.” Transportation, 26(1), 5–30.
Tao, Y., and Xinmiao, Y. (1998). “Fuzzy comprehensive assessment, fuzzy clustering analysis and its application for urban traffic environmental quality evaluation.” Transport. Res. D, 3(1), 51–57.
Tortajada, C. (2006). “Water management in Singapore.” Int. J. Water Resour. Dev., 22(2), 227–240.
Wang, J. J., Jing, Y. Y., Zhang, C. F., and Zhao, J. H. (2009). “Review on multi-criteria decision analysis aid in sustainable energy decision-making.” Renew. Sustain. Energ. Rev., 13(9), 2263–2278.
Yager, R. R. (1977). “Multiple objective decision-making using fuzzy sets.” Int. J. Man-Mach. Stud., 9(4), 375–382.
Yan, J. M., and Vairavamoorthy, K. (2003). “Fuzzy approach for pipe condition assessment.” Proc., ASCE International Conf. on Pipeline Engineering and construction, Baltimore.
Zadeh, L. A. (1965). “Fuzzy sets.” Inf. Control, 8(3), 338–353.
Zahedi, F. (1986). “A simulation study of estimation methods in the analytic hierarchy process.” Socio-Econ. Plann. Sci., 20(6), 347–354.
Zahedi, F. (1988). “The analytic hierarchy process—A survey of the method and its applications.” Interfaces, 16(4), 96–108.
Zimmermann, H. J. (1986). “Multi-criteria decision making in crisp and fuzzy environments.” Fuzzy sets and application, A. Jones et al., eds., Reidel, Norwell, MA.
Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 17 • Issue 4 • December 2011
Pages: 163 - 175
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Feb 7, 2009
Accepted: Apr 22, 2011
Published online: Apr 25, 2011
Published in print: Dec 1, 2011
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.