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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 11, 2015 - Issue 12
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Articles

Post-Pareto optimality approach to enhance budget allocation process for bridge rehabilitation management

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Pages 1565-1582 | Received 14 May 2013, Accepted 17 Oct 2014, Published online: 18 Nov 2014

References

  • American Association of State Highway and Transportation Officials. (1997). AASHTO guide for commonly recognized structural elements. Washington, DC: Subcommittee on Bridges and Structures, Standing Committee on Highways, American Association of State Highway and Transportation Officials.
  • Asian Development Bank Report. (2000). Report and recommendation of the president to the board of directors on a proposed loan and technical assistant grant to the Republic of Tajikistan for the Road Rehabilitation Project. TAJ 32514.
  • Azevedo, J., Guerreiro, L., Bento, R., Lopes, M., & Proenca, J. (2010). Seismic vulnerability of lifelines in the greater Lisbon area. Bulletin of Earthquake Engineering, 8, 157–180. doi:10.1007/s10518-009-9124-7.
  • Bazgan, C., Hugot, H., & Vanderpooten, D. (2007). An efficient implementation for the 0-1 multi-objective knapsack problem. In Experimental algorithms (pp. 406–419). Berlin: Springer. doi:10.1007/978-3-540-72845-0_31.
  • Beasley, J.E. (2004). A population heuristic for constrained two-dimensional non-guillotine cutting. European Journal of Operation Research, 156, 601–627. doi:10.1016/S0377-2217(03)00139-5.
  • Bentley, P.J., & Wakefield, J.P. (1998). Finding acceptable solutions in the Pareto-optimal range using multiobjective genetic algorithms. In Soft computing in engineering design and manufacturing (pp. 231–240). London: Springer-Verlag. doi:10.1007/978-1-4471-0427-8_25.
  • Bjornsson, H.C., De la Garza, J.M., & Nasir, M.J. (2000). A decision support system for road maintenance budget allocation. In Proceedings of computing in civil and building engineering (pp. 702–709). doi:10.1061/40513(279)92.
  • Chan, W.T., Fwa, T.F.F., & Tan, J.Y. (2003). Optimal fund-allocation analysis for multidistrict highway agencies. Journal of Infrastructure Systems, 9, 167–175. doi:10.1061/(ASCE)1076-0342(2003)9:4(167).
  • Chapman, R.E., & Thomas, D.S. (2007). A guide to printed and electronic resources for developing a cost-effective risk mitigation plan for new and existing constructed facilities. NISTIR 7390.
  • Cheng, M., Wu, Y., Chen, S., & Weng, M. (2009). Economic evaluation model for post-earthquake bridge repair/rehabilitation: Taiwan. Automation in Construction, 18, 204–218. doi:10.1016/j.autcon.2008.08.004.
  • Djannaty, F., & Doostdar, S. (2008). A hybrid genetic algorithm for the multidimensional knapsack problem. International Journal of Contemporary Mathematic Sciences, 3, 443–456. doi:10.1007/s11227-014-1268-9.
  • Elbehairy, H., Hegazy, T., & Soudki, K. (2009). Integrated multiple-element bridge management system. Journal of Bridge Engineering, 14, 179–187. doi:10.1061/(ASCE)1084-0702(2009)14:3(179).
  • Elhag, T.M.S., & Wang, Y. (2007). Risk assessment for bridge maintenance projects: Neural networks versus regression techniques. Journal of Computing in Civil Engineering, 21, 402–409. doi:10.1016/(ASCE)0887-3801(2007)21:6(402).
  • Federal Highway Administration. (1995). Seismic retrofitting manual for highway bridges  (Publication No. FHWA-RD-94-052). McLean, VA: Department of Transportation, Federal Highway Administration.
  • Federal Highway Administration. (2008). Seismic retrofitting manual for highway structures. Part 1: Bridges  (MCEER-08-SP02). Washington, DC: Author.
  • Frangopol, D.M., & Liu, M. (2007). Maintenance and management of civil infrastructure based on condition, safety, optimization, and life-cycle cost. Structure and Infrastructure Engineering, 3, 29–41. doi:10.1080/15732470500253164.
  • Furuta, H., Frangopol, D.M., & Nakatsu, K. (2011). Life-cycle cost of civil infrastructure with emphasis on balancing structural performance and seismic risk of road network. Structure and Infrastructure Engineering, 7, 65–74. doi:10.1080/15732471003588346.
  • Furuta, H., Kameda, T., Nakahara, K., Takahashi, Y., & Frangopol, D.M. (2006). Optimal bridge maintenance planning using improved multi-objective genetic algorithm. Structure and Infrastructure Engineering, 2, 33–41. doi:10.1080/15732470500031040.
  • Fwa, T.F., & Farhan, J. (2012). Optimal multi-asset maintenance budget allocation in highway asset management. Journal of Transportation Engineering, 138, 1179–1187. doi:10.1061/(ASCE)TE.1943-5436.0000414.
  • Gharaibeh, N.G., Yi-Chang, C., & Gurian, P.L. (2006). Decision methodology for allocating funds across transportation infrastructure assets. Journal of Infrastructure Systems, 12, 1–9. doi:10.1061/(ASCE)1076-0342(2006)12:1(1).
  • Goel, T., Stander, N., & Yih-Yih, L. (2010). Efficient resource allocation for genetic algorithm based multi-objective optimization with 1000 simulations. Structural Multidisciplinary Optimization, 41, 421–432. doi:10.1007/s00158-009-04269.
  • Gokey, J., Klein, N., & Mackey, C. (2009). Development of a prioritization methodology for maintaining Virginia's bridge infrastructure systems. IEEE systems and information engineering design symposium. Charlottesville, VA: University of Virginia, April 24. 10.1109/SIEDS.
  • Goldberg, D. E. (1988). Genetic algorithms and Walsh functions: A gentle introduction. Clearinghouse for Genetic Algorithms, Department of Mechanical Engineering, University of Alabama.
  • Goldberg, D.E. (1989). Genetic algorithms in search, optimization and machine learning. Toronto: Addison-Wesley.
  • Hristakeva, M., & Shrestha, D. (2004, April). Solving the 0–1 knapsack problem with genetic algorithms. In Proceedings of the 37th midwest instruction and computing symposium, Morris, MN.
  • Hwang, C.L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. New York, NY: Springer-Verlag. doi:10.1016/j.scitotenv.2011.06.022.
  • Iniestra, J.G., & Gutierrez, J.G. (2009). Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework. Applied Soft Computing, 9, 512–526. doi:10.1016/j.asoc.2008.07.006.
  • Jahanshahloo, G.R., Hosseinzadeh, F.L., & Izadikhah, M. (2006). Extension of the TOPSIS method for decision-making problems with fuzzy data. Applied Mathematics and Computation, 181, 1544–1551. doi:10.1016/j.amc.2006.02.057.
  • Karydasa, D.M., & Gifun, J.F. (2006). A method for the efficient prioritization of infrastructure renewal projects. Reliability Engineering and System Safety, 91, 84–99. doi:10.1016/j.ress.2004.11.016.
  • Keeney, R.L., & Raiffa, H. (1993). Decisions with multiple objectives: Preferences and value trade-offs. Cambridge: Cambridge University Press.
  • Kochenberger, G.F. (2003). Handbook of metaheuristics. Dordrecht: Kluwer Academic Publishers.
  • Kong, J.S., & Frangopol, D.M. (2003). Life-cycle reliability-based maintenance cost optimization of deteriorating structures with emphasis on bridges. Journal of Structural Engineering, 129, 818–828. doi:10.1061/(ASCE)0733-9445(2003)129:6(818).
  • Korhonen, P., & Halme, M. (1990). Supporting the decision maker to find the most preferred solutions for a MOLP-problem. Proceedings of the 9th international conference on multiple criteria decision making, Fairfax, VA, pp. 173–183.
  • Kulturel-Konak, S., Coit, D.W., & Baheranwala, F. (2008). Pruned Pareto-optimal sets for the system redundancy allocation problem based on multiple prioritized objectives. Journal of Heuristics, 14, 335–357. doi:10.1007/s10732-007-9041-3.
  • Lai, Y.J., Liu, T.Y., & Hwang, C.L. (1994). TOPSIS for MODM. European Journal of Operational Research, 76, 486–500. doi:10.1016/0377-2217(94)90282-8.
  • Lee, C.K., & Kim, S.K. (2007). GA-based algorithm for selecting optimal repair and rehabilitation methods for reinforced concrete (RC) bridge decks. Automation in Construction, 16, 153–164. doi:10.1016/j.autcon.2006.03.001.
  • Lee, J. (2007). A methodology for developing bridge condition rating models based on limited inspection records  (Doctoral dissertation, Griffith University, Nathan, Queensland, Australia).
  • Liu, C., Hammad, A., & ltoh, Y. (1997). Maintenance strategy optimization of bridge decks using genetic algorithm. Journal of Transportation Engineering, 123, 91–100. doi:10.1061/(ASCE)0733-947X(1997)123:2(91).
  • Liu, M., & Frangopol, D.M. (2005). Bridge annual maintenance prioritization under uncertainty by multiobjective combinatorial optimization. Computer-Aided Civil and Infrastructure Engineering, 20, 343–353. doi:10.1111/j.1467-8667.2005.00401.x.
  • Liu, M., & Frangopol, D.M. (2006). Optimizing bridge network maintenance management under uncertainty with conflicting criteria: Life-cycle maintenance, failure, and user costs. Journal of Structural Engineering, 132, 1835–1845. doi:10.1061/(ASCE)0733-9445(2006)132:11(1835).
  • Lust, T., & Teghem, J. (2012). The multiobjective multidimensional knapsack problem: A survey and a new approach. International Transactions in Operational Research, 19, 495–520.
  • Memtsas, D.P. (2003). Multiobjective programming methods in the reserve selection problem. European Journal of Operational Research, 150, 640–652. doi:10.1016/s0377-2217(02)00519-2.
  • Moore, G.D. (1994). Resource road rehabilitation handbook: Planning and implementation guidelines (interim methods). Watershed Restoration Technical Circular, 3.
  • Morcous, G. (2007). Pareto analysis for multicriteria optimization of bridge preservation decisions. Transportation Research Record: Journal of the Transportation Research Board, 1991, 62–68. 10.3141/1991-08.
  • National Cooperative Highway Research Program. (2007). Multi-objective optimization for bridge management systems  (Report No. 590). Washington, DC: National Cooperative Highway Research Program Synthesis, Transportation Research Board.
  • Okasha, N., & Frangopol, D. (2010). Novel approach for multicriteria optimization of life-cycle preventive and essential maintenance of deteriorating structures. Journal of Structural Engineering, 136, 1009–1022. doi:10.1061/(ASCE)ST.1943-541X.0000198.
  • Okasha, N.M., & Frangopol, D.M. (2009). Lifetime-oriented multi-objective optimization of structural maintenance considering system reliability, redundancy and life-cycle cost using GA. Structural Safety, 31, 460–474. doi:10.1016/j.strusafe.2009.06.005.
  • Orcesi, A.D., & Cremona, C.F. (2010). A bridge network maintenance framework for Pareto optimization of stakeholders/users costs. Reliability Engineering and System Safety, 95, 1230–1243. doi:10.1016/j.ress.2010.06.013.
  • Orcesi, A.D., & Frangopol, D.M. (2011a). Optimization of bridge maintenance strategies based on structural health monitoring information. Structural Safety, 33, 26–41. doi:10.1016/j.strusafe.2010.05.002.
  • Orcesi, A.D., & Frangopol, D.M. (2011b). Probability-based multiple-criteria optimization of bridge maintenance using monitoring and expected error in the decision process. Structural and Multidisciplinary Optimization, 44, 137–148. doi:10.1007/s00158-010-0613-8.
  • Padgett, J.E., Dennemann, K., & Ghosh, J. (2010). Risk-based seismic life-cycle cost–benefit analysis for bridge retrofit assessment. Structural Safety, 32, 165–173. doi:10.1016/j.strusafe.2009.10.003.
  • Perng, Y.H., Juan, Y.K., & Hsu, H.S. (2007). Genetic algorithm-based decision support for the restoration budget allocation of historical buildings. Building and Environment, 42, 770–778. doi:10.1016/j.buildenv.2005.09.009.
  • Petcherdchoo, A., Neves, L.A., & Frangopol, D.M. (2008). Optimizing lifetime condition and reliability of deteriorating structures with emphasis on bridges. Journal of Structural Engineering, 134, 544–552. doi:10.1061/(ASCE)0733-9445(2008)134:4(544).
  • Pravinvongvuth, S., Chootinan, P., Chen, A., & Narupiti, S. (2005). A methodology for selecting Pareto optimal solutions developed by a multiobjective AVI reader location model. Journal of the Eastern Asia Society for Transportation Studies, 6, 2441–2456. doi:10.1061/(ASCE)0733-947X(1998)124:2(172).
  • Rothley, K.D. (1999). Designing bioreserve networks to satisfy multiple, conflicting demands. Ecological Applications, 9, 741–750. doi:10.1890/1051-0761(1999)009[0741:DBNTSM]2.0.CO;2.
  • Saaty, T.L. (2008). Relative measurement and its generalization in decision making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process. RACSAM-Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas, 102, 251–318. doi:10.1007/BF03191825.
  • Sharma, V., Al-Hussein, M., Safouhi, H., & Bouferguene, A. (2008). Municipal infrastructure asset levels of service assessment for investment decisions using analytic hierarchy process. Journal of Infrastructure Systems, 14, 193–200. doi:10.1061/(ASCE)1076-0342(2008)14:3(193).
  • Shepard, R.W., & Johnson, M.B. (2001). California bridge health index: A diagnostic tool to maximize bridge longevity, investment. TR News, 215, July–August, Transportation Research Board. http://onlinepubs.trb.org/onlinepubs/trnews/trnews215full.pdf.
  • Shinozuka, M., Murachi, Y., Dong, X., Zhou, Y., & Orlikowski, M.J. (2003). Effect of seismic retrofit of bridges on transportation networks. Earthquake Engineering and Engineering Vibration, 2, 169–179.
  • Shohet, I.M., & Perelstein, E. (2004). Decision support model for the allocation of resources in rehabilitation projects. Journal of Construction Engineering and Management, 130, 249–257. doi:10.1061/(ASCE)0733-9364(2004)130:2(249).
  • Srinivas, N., & Deb, K. (1994). Multiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary Computation, 2, 221–248. doi:10.1162/evco.1994.2.3.221.
  • Taboada, H., & Coit, D. (2005). Post-Pareto optimality analysis to efficiently identify promising solutions for multi-objective problems. Rutgers University ISE Working Paper, 5–15. https://doi.org/doi:10.1080/07408170701781951.
  • Taleizadeh, A.A., Niaki, S.T.A., & Aryanezhad, M.B. (2009). A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy replenishments. Mathematical and Computer Modelling, 49, 1044–1057. doi:10.1016/j.mcm.2008.10.013.
  • Tan, J.Y., Chan, W.T., & Fwa, T.F. (2004). Interactive budget allocation concept for pavement management. Proceedings of the 6th international conference on managing pavements, Queensland, Australia.
  • Thompson, P.D., & Shepard, R.W. (2000, June). AASHTO Commonly-recognized bridge elements. In Successful application and lesson learned. Prepared for the national workshop on commonly recognized measures for maintenance, Scottsdale, Arizona.
  • Torrisi, G. (2009). Public infrastructure: Definition, classification and measurement issues  (Munich Personal RePEc Archive, MPRA Paper No. 12990). Available at http://mpra.ub.uni-muenchen.de/12990/.
  • U.S. Department of Transportation. (1999). Asset management primer. Washington, DC: U.S. Department of Transportation, Federal Highway Administration, Office of Asset Management.
  • Venkat, V., Jacobson, S., & Stori, J. (2004). A post-optimality analysis algorithm for multi-objective optimization. Computational Optimization and Applications, 28, 357–372. doi:10.1023/B:COAP.0000033968.55439.8b.
  • Yadollahi, M., & Zin, M.R. (2014). Multi-strategy budget allocation decision support system for seismic rehabilitation of road infrastructure. Structure and Infrastructure Engineering, 10, 239–260. doi:10.1080/15732479.2012.737810.
  • Yager, R.R. (2004). Modelling prioritized multicriteria decision making. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 34. doi:10.1016/j.cie.2013.06.007.
  • Yoon, K.P. (1987). A reconciliation among discrete compromise solutions. Journal of the Operational Research Society, 38, 277–286. 10.1057/jors.1987.44.
  • Zio, E., & Bazzo, R. (2012). A comparison of methods for selecting preferred solutions in multi-objective decision making. In Computational intelligence systems in industrial engineering (pp. 23–43). Amsterdam, Netherlands: Atlantis Press. doi:10.2991/978-94-91216-77-0_2.

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