An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed.Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners onwhen and howto apply availablemethods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.The authors gratefully acknowledge members of the research group at the Pontificia Universidad Catolica de Chile for their contributions and resources during the study. The research team acknowledges Conicyt-Fondef/Decimoseptimo Concurso de Proyectos de Investigacion y Desarrollo del Fondo de Fomento al Desarrollo Cientifico y Tecnologico, Fondef/Conicyt 2009 (D09I1018) for funding this project. Support of the associated institutions is also appreciated: Ministry of Housing and Urban Development (Ministerio de Vivienda y Urbanismo), Regional Government for Metropolitan Region (Gobierno Regional de la Region Metropolitana), Municipality of Santiago (Municipalidad de Santiago), and Municipality of Macul (Municipalidad de Macul). Funding over Santander Universidades (Becas Iberoamerica Jovenes Profesionales e Investigadores, 2013) to support this work is sincerely appreciated.Torres Machí, C.; Chamorro, A.; Videla, C.; Pellicer Armiñana, E.; Yepes, V. (2014). An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level. Scientific World Journal. 2014(4329):1-11. https://doi.org/10.1155/2014/52432911120144329Qin, J., Ni, L., & Shi, F. (2013). Mixed Transportation Network Design under a Sustainable Development Perspective. The Scientific World Journal, 2013, 1-8. doi:10.1155/2013/549735Chamorro, A., & Tighe, S. L. (2009). Development of a Management Framework for Rural Roads in Developing Countries. Transportation Research Record: Journal of the Transportation Research Board, 2093(1), 99-107. doi:10.3141/2093-12Golroo, A., & L. Tighe, S. (2012). Optimum Genetic Algorithm Structure Selection in Pavement Management. Asian Journal of Applied Sciences, 5(6), 327-341. doi:10.3923/ajaps.2012.327.341Hsueh, S.-L., & Yan, M.-R. (2013). A Multimethodology Contractor Assessment Model for Facilitating Green Innovation: The View of Energy and Environmental Protection. The Scientific World Journal, 2013, 1-14. doi:10.1155/2013/624340Jiao, Y., Liu, H., Zhang, P., Wang, X., & Wei, H. (2013). Unsupervised Performance Evaluation Strategy for Bridge Superstructure Based on Fuzzy Clustering and Field Data. The Scientific World Journal, 2013, 1-6. doi:10.1155/2013/427072Shah, Y. U., Jain, S. S., & Parida, M. (2012). Evaluation of prioritization methods for effective pavement maintenance of urban roads. International Journal of Pavement Engineering, 15(3), 238-250. doi:10.1080/10298436.2012.657798De la Garza, J. M., Akyildiz, S., Bish, D. R., & Krueger, D. A. (2011). Network-level optimization of pavement maintenance renewal strategies. Advanced Engineering Informatics, 25(4), 699-712. doi:10.1016/j.aei.2011.08.002Gao, L., Xie, C., Zhang, Z., & Waller, S. T. (2011). Network-Level Road Pavement Maintenance and Rehabilitation Scheduling for Optimal Performance Improvement and Budget Utilization. Computer-Aided Civil and Infrastructure Engineering, 27(4), 278-287. doi:10.1111/j.1467-8667.2011.00733.xAmador-Jiménez, L. E., & Mrawira, D. (2009). Roads Performance Modeling and Management System from Two Condition Data Points: Case Study of Costa Rica. Journal of Transportation Engineering, 135(12), 999-1007. doi:10.1061/(asce)te.1943-5436.0000074Gao, L., & Zhang, Z. (2008). Robust Optimization for Managing Pavement Maintenance and Rehabilitation. Transportation Research Record: Journal of the Transportation Research Board, 2084(1), 55-61. doi:10.3141/2084-07Ng, M., Zhang, Z., & Travis Waller, S. (2011). The price of uncertainty in pavement infrastructure management planning: An integer programming approach. Transportation Research Part C: Emerging Technologies, 19(6), 1326-1338. doi:10.1016/j.trc.2011.03.003Ferreira, A., Antunes, A., & Picado-Santos, L. (2002). Probabilistic Segment-linked Pavement Management Optimization Model. Journal of Transportation Engineering, 128(6), 568-577. doi:10.1061/(asce)0733-947x(2002)128:6(568)Yoo, J., & Garcia-Diaz, A. (2008). Cost-effective selection and multi-period scheduling of pavement maintenance and rehabilitation strategies. Engineering Optimization, 40(3), 205-222. doi:10.1080/03052150701686937Farhan, J., & Fwa, T. F. (2012). Incorporating Priority Preferences into Pavement Maintenance Programming. Journal of Transportation Engineering, 138(6), 714-722. doi:10.1061/(asce)te.1943-5436.0000372Fwa, T. F., & Farhan, J. (2012). Optimal Multiasset Maintenance Budget Allocation in Highway Asset Management. Journal of Transportation Engineering, 138(10), 1179-1187. doi:10.1061/(asce)te.1943-5436.0000414Tsunokawa, 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.xChou, J.-S., & Le, T.-S. (2011). Reliability-based performance simulation for optimized pavement maintenance. Reliability Engineering & System Safety, 96(10), 1402-1410. doi:10.1016/j.ress.2011.05.005Flintsch, G. W., & Chen, C. (2004). Soft Computing Applications in Infrastructure Management. Journal of Infrastructure Systems, 10(4), 157-166. doi:10.1061/(asce)1076-0342(2004)10:4(157)Chan, W. T., Fwa, T. F., & Tan, J. Y. (2003). Optimal Fund-Allocation Analysis for Multidistrict Highway Agencies. Journal of Infrastructure Systems, 9(4), 167-175. doi:10.1061/(asce)1076-0342(2003)9:4(167)Chootinan, P., Chen, A., Horrocks, M. R., & Bolling, D. (2006). A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach. Transportation Research Part A: Policy and Practice, 40(9), 725-743. doi:10.1016/j.tra.2005.12.003Meneses, S., & Ferreira, A. (2013). Pavement maintenance programming considering two objectives: maintenance costs and user costs. International Journal of Pavement Engineering, 14(2), 206-221. doi:10.1080/10298436.2012.727994Fwa, T. F., & Chan, W. T. (1993). Priority Rating of Highway Maintenance Needs by Neural Networks. Journal of Transportation Engineering, 119(3), 419-432. doi:10.1061/(asce)0733-947x(1993)119:3(419)Moazami, D., Behbahani, H., & Muniandy, R. (2011). Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic. Expert Systems with Applications, 38(10), 12869-12879. doi:10.1016/j.eswa.2011.04.079Khurshid, M. B., Irfan, M., Ahmed, A., & Labi, S. (2013). Multidimensional benefit–cost evaluation of asphaltic concrete overlays of rigid pavements. Structure and Infrastructure Engineering, 10(6), 792-810. doi:10.1080/15732479.2013.767842Khurshid, M. B., Irfan, M., & Labi, S. (2009). Comparison of Methods for Evaluating Pavement Interventions. Transportation Research Record: Journal of the Transportation Research Board, 2108(1), 25-36. doi:10.3141/2108-03Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. doi:10.1126/science.220.4598.671Martí, J. V., Gonzalez-Vidosa, F., Yepes, V., & Alcalá, J. (2013). Design of prestressed concrete precast road bridges with hybrid simulated annealing. Engineering Structures, 48, 342-352. doi:10.1016/j.engstruct.2012.09.01