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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 19, 2023 - Issue 6
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Article

A hybrid genetic algorithm to maintain road networks using reliability theory

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Pages 810-823 | Received 23 Feb 2021, Accepted 04 Aug 2021, Published online: 26 Sep 2021

References

  • AASHTO. (2012). Pavement management guide (2nd ed.). Washington, DC: American Association of State Highway and Transportation Officials.
  • Abaza, K. A. (2016). Back-calculation of transition probabilities for Markovian-based pavement performance prediction models. International Journal of Pavement Engineering, 17(3), 253–264. ‏ doi:10.1080/10298436.2014.993185
  • Abaza, K. A. (2017). Empirical approach for estimating the pavement transition probabilities used in non-homogenous Markov chains. International Journal of Pavement Engineering, 18(2), 128–137. doi:10.1080/10298436.2015.1039006
  • Abaza, K. A. (2018). Empirical-Markovian model for predicting the overlay design thickness for asphalt concrete pavement. Road Materials and Pavement Design, 19(7), 1617–1635. ‏ doi:10.1080/14680629.2017.1338188
  • Affenzeller, M., Wagner, S., Winkler, S., & Beham, A. (2009). Genetic algorithms and genetic programming: Modern concepts and practical applications. Boca Raton, FL: CRC Press.
  • Ahadi, K., & Sullivan, K. M. (2020). Approximate dynamic programming for selective maintenance in series–Parallel systems. IEEE Transactions on Reliability, 69(3), 1147–1164. ‏ doi:10.1109/TR.2019.2916898
  • Altarabsheh, A., Kandil, A., & Ventresca, M. (2016). Multi-objective optimization algorithm for sewer network rehabilitation using life cycle cost analysis and semi-Markov deterioration models. In Construction Research Congress 2016 (pp. 2089–2099). doi:10.1061/9780784479827.208
  • Altarabsheh, A., Altarabsheh, R., Altarabsheh, S., & Asi, I. (2020). Prediction of pavement performance using multistate survival models. Journal of Transportation Engineering, Part B: Pavements, 147(1), 04020082.
  • Altarabsheh, A., Ventresca, M., & Kandil, A. (2018). New approach for critical pipe prioritization in wastewater asset management planning. Journal of Computing in Civil Engineering, 32(5), 04018044. doi:10.1061/(ASCE)CP.1943-5487.0000784
  • Altarabsheh, A., Ventresca, M., Kandil, A., & Abraham, D. (2019). Markov chain modulated Poisson process to stimulate the number of blockages in sewer networks. Canadian Journal of Civil Engineering, 46(12), 1174–1186. doi:10.1139/cjce-2018-0104
  • Amin, S. R., & Amador-Jiménez, L. E. (2017). Backpropagation Neural Network to estimate pavement performance: Dealing with measurement errors. Road Materials and Pavement Design, 18(5), 1218–1238. doi:10.1080/14680629.2016.1202129
  • Bai, Y., Gungor, O. E., Hernandez-Urrea, J. A., Ouyang, Y., & Al-Qadi, I. L. (2015). Optimal pavement design and rehabilitation planning using a mechanistic-empirical approach. EURO Journal on Transportation and Logistics, 4(1), 57–73. doi:10.1007/s13676-014-0072-2
  • Chan, W. T., Fwa, T. F., & Hoque, K. Z. (2001). Constraint handling methods in pavement maintenance programming. Transportation Research Part C: Emerging Technologies, 9(3), 175–190. doi:10.1016/S0968-090X(00)00023-1
  • Gao, H., & Zhang, X. (2013). A Markov‐based road maintenance optimization model considering user costs. Computer-Aided Civil and Infrastructure Engineering, 28(6), 451–464. ‏ doi:10.1111/mice.12009
  • Gillespie, T. D. (1992). Everything you always wanted to know about the IRI, but were afraid to ask. In Proceedings of the road profile users group meeting (pp. 1–13). Lincoln, NE: University of Michigan Transportation Research Institute.
  • Herrmann, A. W. (2013, May). ASCE 2013 report card for America's infrastructure. IABSE symposium report (Vol. 99, No. 33, pp. 9–10). International Association for Bridge and Structural Engineering.
  • Hwang, F. K., & Yao, Y. C. (1989). Multistate consecutively-connected systems. IEEE Transactions on Reliability, 38(4), 472–474. ‏ doi:10.1109/24.46467
  • Ihs, A., & Magnusson, G. (2000). The significance of various road surface properties for traffic and surroundings. Linköping, Sweden: Statens vägoch transport forsknings institut.
  • Irfan, M., Khurshid, M. B., Bai, Q., Labi, S., & Morin, T. L. (2012). Establishing optimal project-level strategies for pavement maintenance and rehabilitation – A framework and case study. Engineering Optimization, 44(5), 565–589. ‏ doi:10.1080/0305215X.2011.588226
  • Jones, R. (2015). Optimizing your road maintenance dollars. Utah Local Technical Assistance Program, 28(1), 2–3.
  • Khatab, A., Aghezzaf, E. H., Diallo, C., & Djelloul, I. (2017). Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations. International Journal of Production Research, 55(10), 3008–3024. ‏ doi:10.1080/00207543.2017.1290295
  • Labi, S., & Sinha, K. (2003). The effectiveness of maintenance and its impact on capital expenditures. Joint Transportation Research Program, 3, 208. ‏
  • Lee, J., & Madanat, S. (2015). A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction. Transportation Research Part B: Methodological, 78, 106–122. doi:10.1016/j.trb.2015.05.001
  • Lee, J., & Madanat, S. (2017). Optimal policies for greenhouse gas emission minimization under multiple agency budget constraints in pavement management. Transportation Research Part D: Transport and Environment, 55, 39–50. doi:10.1016/j.trd.2017.06.009
  • Lee, J., Madanat, S., & Reger, D. (2016). Pavement systems reconstruction and resurfacing policies for minimization of life‐cycle costs under greenhouse gas emissions constraints. Transportation Research Part B: Methodological, 93, 618–630. doi:10.1016/j.trb.2016.08.016
  • Levitin, G., Xing, L., & Dai, Y. (2015). Linear multistate consecutively-connected systems subject to a constrained number of gaps. Reliability Engineering & System Safety, 133, 246–252. ‏ doi:10.1016/j.ress.2014.09.004
  • Li, N., Haas, R., & Xie, W. C. (1997). Development of a new asphalt pavement performance prediction model. Canadian Journal of Civil Engineering, 24(4), 547–559. ‏ doi:10.1139/l97-001
  • Ma, J., Cheng, L., & Li, D. (2018). Road maintenance optimization model based on dynamic programming in urban traffic network. Journal of Advanced Transportation, 2018, 1–11. doi:10.1155/2018/4539324
  • Macchi, M., Garetti, M., Centrone, D., Fumagalli, L., & Pavirani, G. P. (2012). Maintenance management of railway infrastructures based on reliability analysis. Reliability Engineering & System Safety, 104, 71–83. ‏ doi:10.1016/j.ress.2012.03.017
  • Mao, X., Yuan, C., & Gan, J. (2019). Incorporating dynamic traffic distribution into pavement maintenance optimization model. Sustainability, 11(9), 2488. doi:10.3390/su11092488
  • Martello, S., Pisinger, D., & Toth, P. (1999). Dynamic programming and strong bounds for the 0-1 knapsack problem. Management Science, 45(3), 414–424. ‏ doi:10.1287/mnsc.45.3.414
  • Mathew, B. S., & Isaac, K. P. (2014). Optimisation of maintenance strategy for rural road network using genetic algorithm. International Journal of Pavement Engineering, 15(4), 352–360. doi:10.1080/10298436.2013.806807
  • Mubaraki, M. (2016). Highway subsurface assessment using pavement surface distress and roughness data. International Journal of Pavement Research and Technology, 9(5), 393–402. doi:10.1016/j.ijprt.2016.10.001
  • Peng, R., Zhai, Q., Xing, L., & Yang, J. (2016). Reliability analysis and optimal structure of series-parallel phased-mission systems subject to fault-level coverage. IIE Transactions, 48(8), 736–746. ‏ doi:10.1080/0740817X.2016.1146424
  • Pérez-Acebo, H., Bejan, S., & Gonzalo-Orden, H. (2018). Transition probability matrices for flexible pavement deterioration models with half-year cycle time. International Journal of Civil Engineering, 16(9), 1045–1056. doi:10.1007/s40999-017-0254-z
  • Pérez-Acebo, H., Gonzalo-Orden, H., Findley, D. J., & Rojí, E. (2021). Modeling the international roughness index performance on semi-rigid pavements in single carriageway roads. Construction and Building Materials, 272, 121665. ‏ doi:10.1016/j.conbuildmat.2020.121665
  • Pérez-Acebo, H., Mindra, N., Railean, A., & Rojí, E. (2019). Rigid pavement performance models by means of Markov Chains with half-year step time. International Journal of Pavement Engineering, 20(7), 830–843. ‏ doi:10.1080/10298436.2017.1353390
  • Pootakham, T., & Kumar, A. (2010). A comparison of pipeline versus truck transport of bio-oil. Bioresource Technology, 101(1), 414–421. ‏ doi:10.1016/j.biortech.2009.07.077
  • Santos, J., Ferreira, A., & Flintsch, G. (2019). An adaptive hybrid genetic algorithm for pavement management. International Journal of Pavement Engineering, 20(3), 266–286. doi:10.1080/10298436.2017.1293260
  • Santos, J., Torres-Machi, C., Morillas, S., & Cerezo, V. (2020). A fuzzy logic expert system for selecting optimal and sustainable life cycle maintenance and rehabilitation strategies for road pavements. International Journal of Pavement Engineering, 1–13. ‏ doi:10.1080/10298436.2020.1751161
  • Sayers, M. W., & Karamihas, S. M. (1998). The little book of profiling. Ann Arbor, MI: University of Michigan.‏
  • Sayers, M. W., Gillespie, T. D., & Paterson, W. D. O. (1986). Guideline for the conduct and calibration of road roughness measurements. The World Bank, Technical Paper, 46. Washington, DC.
  • Schroten, A., van Wijngaarden, L., Brambilla, M., Gatto, M., Maffii, S., Trosky, F., Kramer, H., Monden, R., Bertschmann, D., Killer, M., Lambla, V., El Beyrouty, K., & Amaral, S. (2019). Overview of transport infrastructure expenditures and costs. Publications Office of the European Union.
  • Soszynska, J. (2010). Reliability and risk evaluation of a port oil pipeline transportation system in variable operation conditions. International Journal of Pressure Vessels and Piping, 87(2–3), 81–87. ‏ doi:10.1016/j.ijpvp.2010.01.002
  • Tabatabaee, N., & Ziyadi, M. (2013). Bayesian approach to updating Markov-based models for predicting pavement performance. Transportation Research Record: Journal of the Transportation Research Board, 2366(1), 34–42. ‏ doi:10.3141/2366-04
  • Torres-Machi, C., Pellicer, E., Yepes, V., & Chamorro, A. (2017). Towards a sustainable optimization of pavement maintenance programs under budgetary restrictions. Journal of Cleaner Production, 148, 90–102. ‏ doi:10.1016/j.jclepro.2017.01.100
  • Tsunokawa, K., Van Hiep, D., & Ul‐Islam, R. (2006). True optimization of pavement maintenance options with what‐if models. Computer-Aided Civil and Infrastructure Engineering, 21(3), 193–204. doi:10.1111/j.1467-8667.2006.00427.x
  • Uddin, W. (2006). Pavement management systems. In T. F. Fwa (Ed.), The handbook of highway engineering. Boca Raton, FL: Taylor & Francis.
  • Ushakov, I. A. (1986). A universal generating functions. Soviet Journal of Computer and Systems Sciences, 24(5), 118–129.
  • Walls, J., III, & Smith, M. R. (1998). Life cycle cost analysis in pavement design-interim technical bulletin (No. FHWA-SA-98-061). Washington, DC. Federal Highway Administration.‏
  • Xiang, Y., Levitin, G., & Dai, Y. (2012). Linear multistate consecutively-connected systems with gap constraints. IEEE Transactions on Reliability, 61(1), 208–214. ‏ doi:10.1109/TR.2011.2182393
  • Yeh, W. C. (2002). Multistate-node acyclic network reliability evaluation. Reliability Engineering & System Safety, 78(2), 123–129. ‏ doi:10.1016/S0951-8320(02)00114-X
  • Yu, B., Lu, Q., & Xu, J. (2013). An improved pavement maintenance optimization methodology: Integrating LCA and LCCA. Transportation Research Part A: Policy and Practice, 55, 1–11.
  • Yu, H., Yang, J., Peng, R., & Zhao, Y. (2016). Reliability evaluation of linear multi-state consecutively-connected systems constrained by m consecutive and n total gaps. Reliability Engineering & System Safety, 150, 35–43. ‏ doi:10.1016/j.ress.2016.01.010
  • Zhang, X., & Gao, H. (2012). Road maintenance optimization through a discrete-time semi-Markov decision process. Reliability Engineering & System Safety, 103, 110–119. doi:10.1016/j.ress.2012.03.011
  • Zhang, Y., Bigham, J., Ragland, D., & Chen, X. (2015). Investigating the associations between road network structure and non-motorist accidents. Journal of Transport Geography, 42, 34–47. doi:10.1016/j.jtrangeo.2014.10.010
  • Zhao, Z., Xiao, B., Wang, N., Yan, X., & Ma, L. (2019a). Selective maintenance optimization for a multi-state system considering human reliability. Symmetry, 11(5), 652. ‏ doi:10.3390/sym11050652
  • Zhao, Z., Xiao, B., Wang, N., Yan, X., & Ma, L. (2019b). Selective maintenance optimization for a multi-state system with degradation interaction. IEEE Access., 7, 99191–99206. ‏ doi:10.1109/ACCESS.2019.2927683
  • Zhou, Y., Lin, T. R., Sun, Y., Bian, Y., & Ma, L. (2015). An effective approach to reducing strategy space for maintenance optimisation of multistate series–parallel systems. Reliability Engineering & System Safety, 138, 40–53. ‏ doi:10.1016/j.ress.2015.01.018

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