Bridge Risk Assessment

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Computers & Industrial Engineering 54 (2008) 513–525

An integrated AHP–DEA methodology for bridge risk assessment q Ying-Ming Wang
a b


, Jun Liu b, Taha M.S. Elhag



Institute of Soft Science, Fuzhou University, Fuzhou 350002, PR China School of Computing and Mathematics, Faculty of Engineering, University of Ulster at Jordanstown, Shore Road, Newtownabbey, Co. Antrim BT37 0QB, Northern Ireland, UK School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, P.O. Box 88, Manchester M60 1QD, UK Received 14 January 2006; received in revised form 5 September 2007; accepted 6 September 2007 Available online 14 September 2007

Abstract The traditional analytic hierarchy process (AHP) method can only compare a very limited number of decision alternatives, which is usually not more than 15. When there are hundreds or thousands of alternatives to be compared, the pairwise comparison manner provided by the traditional AHP is obviously infeasible. In this paper we propose an integrated AHP–DEA methodology to evaluate bridge risks of hundreds or thousands of bridge structures, based on which the maintenance priorities of the bridge structures can be decided. The proposed AHP–DEA methodology uses the AHP to determine the weights of criteria, linguistic terms such as High, Medium, Low and None to assess bridge risks under each criterion, the data envelopment analysis (DEA) method to determine the values of the linguistic terms, and the simple additive weighting (SAW) method to aggregate bridge risks under different criteria into an overall risk score for each bridge structure. The integrated AHP–DEA methodology is applicable to any number of decision alternatives and is illustrated with a numerical example. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: Bridge risk assessment; Analytic hierarchy process; Data envelopment analysis; Maintenance priority

1. Introduction Bridge risk assessment is often conducted to determine the priority of bridge structures for maintenance. For example, Adey, Hajdin, and Bruhwiler (2003) presented a risk-based approach to determining the optimal ¨ intervention for a bridge subject to multiple hazards. Johnson and Niezgoda (2004) presented a risk-based method for ranking, comparing and choosing the most appropriate bridge scour countermeasures using the

This research was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under the Grant No. GR/ S66770/01 and also supported by the National Natural Science Foundation of China (NSFC) under the Grant No. 70771027. * Corresponding author. Tel.: +86 591 87893307; fax: +86 591 87892545. E-mail address: (Y.-M. Wang). 0360-8352/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.cie.2007.09.002



Y.-M. Wang et al. / Computers & Industrial Engineering 54 (2008) 513–525

risk priority numbers (PRNs) in failure modes and effects analysis (FMEA). Stein, Young, Trent, and Pearson (1999) developed a risk-based method for assessing the risk associated with scour threat to bridge foundations. The risk of scour failure was defined as the product of the probability of scour failure or heavy damage and the cost associated with failure, adjusted by a risk adjustment factor based on foundation type and type of span. Shetty, Chubb, Knowles, and Halden (1996) proposed a risk-based framework for assessment and prioritization of bridges in need of remedial work, which involves risk evaluation, rankings of bridges in terms of risk, design of remedial action for each bridge, and optimal allocation of resources for remedial work on different bridges. Risk is quantified as the product of probability of failure and consequences of failure. Lounis (2004) presented a risk-based approach for bridge maintenance optimization that takes into account several and possibly...
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