Abstract
Pavement Management Systems (PMS) can benefit the highway agencies in several ways both at network and project levels, especially in selecting cost-effective alternatives. Whether it is new construction, maintenance, or rehabilitation, PMS helps the authorities attain the best possible utilisation of available resources and public money. This investigative paper proposes a network level PMS for the roads of Tiruchirappalli city, India. Data pertaining to inventory, traffic, maintenance history, and serviceability of the study roads are gathered at regular intervals for a period of 7 years. The pavement sections are grouped into homogeneous clusters by k-means clustering, and Multiple Linear Regression Models are developed for the clusters to predict pavement performance. Based on the pavement condition, different maintenance treatments are identified through expert opinion surveys. An optimisation programme UPMMS-GAMS is developed using Generic Algebraic Modelling System (GAMS) software, to consolidate the city's PMS. Pavement condition, age, maintenance options, and maintenance cost are given as model inputs. Minimum performance levels and the maximum number of maintenance activities are constraints that must be guaranteed. The optimisation programme defines the maintenance and rehabilitation strategies to be employed each year to maintain the pavement sections above a minimum desired level.
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References
Hudson, W. R., Haas, R., & Pedigo, R. D. (1979). Pavement management system development. National Cooperative Highway Research Program Report 215. Retrieved February 12, 2021, from http://onlinepubs.trb.org/Onlinepubs/nchrp/nchrp_rpt_215.pdf.
Hudson, W. R., & N.C.H.R. Program., Materials Research & Development Inc. (1968). Systems approach to pavement design: system formulation, performance definition, and material characterization. Oakland: Materials Research & Development Inc.
Haas, R. C. G., & Hudson, W. R. (1978). Pavement management systems. McGraw-Hill Inc.
Watanatada, T. (1987). The highway design and maintenance standards model, 2 v. Retrieved February 12, 2021, from http://digitallibrary.un.org/record/23540.
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. https://doi.org/10.1080/0305215X.2011.588226
Farhan, J., & Fwa, T. F. (2013). Evaluation of effects of priority preferences on optimal resource allocation in pavement management. Advanced Materials Research. https://doi.org/10.4028/www.scientific.net/AMR.723.838
Chi, S., Hwang, J., Arellano, M., Zhang, Z., & Murphy, M. (2013). Development of network-level project screening methods supporting the 4-year pavement management plan in Texas. Journal of Management in Engineering. https://doi.org/10.1061/(asce)me.1943-5479.0000158
Golroo, A., & Tighe, S. L. (2012). Optimum genetic algorithm structure selection in pavement management. Asian Journal of Applied Sciences. https://doi.org/10.3923/ajaps.2012.327.341
Li, N. (1997). PhD Thesis_Development of a probabilistic based, integrated pavement management system
Fwa, T. F., Chan, W. T., & Hoque, K. Z. (1998). Network level programming for pavement management using genetic algorithms. In: 4th International conference on management pavement
Ferreira, A., Picado-Santos, L., & Antunes, A. (2002). A segment-linked optimization model for deterministic pavement management systems. International Journal of Pavement Engineering. https://doi.org/10.1080/10298430290030603
Morcous, G., & Lounis, Z. (2005). Maintenance optimization of infrastructure networks using genetic algorithms. Automation in Construction. https://doi.org/10.1016/j.autcon.2004.08.014
Mathew, B. S., & Isaac, K. P. (2014). Optimisation of maintenance strategy for rural road network using genetic algorithm. International Journal of Pavement Engineering. https://doi.org/10.1080/10298436.2013.806807
Meneses, S., & Ferreira, A. (2015). Flexible pavement maintenance programming considering the minimisation of maintenance and rehabilitation costs and the maximisation of the residual value of pavements. International Journal of Pavement Engineering. https://doi.org/10.1080/10298436.2014.943207
Saha, P., & Ksaibati, K. (2016). A risk-based optimisation methodology for pavement management system of county roads. International Journal of Pavement Engineering. https://doi.org/10.1080/10298436.2015.1065992
Augeri, M. G., Greco, S., & Nicolosi, V. (2019). Planning urban pavement maintenance by a new interactive multiobjective optimization approach. European Transport Research Review. https://doi.org/10.1186/s12544-019-0353-9
Mataei, B., Nejad, F. M., & Zakeri, H. (2021). Pavement maintenance and rehabilitation optimization based on cloud decision tree. International Journal of Pavement Research and Technology. https://doi.org/10.1007/s42947-020-0306-7
Janani, L., Dixit, R. K., Sunitha, V., & Mathew, S. (2019). Prioritisation of pavement maintenance sections deploying functional characteristics of pavements. International Journal of Pavement Engineering, 21(14), 1815–1822. https://doi.org/10.1080/10298436.2019.1567923
Kuhn, K. D., & Madanat, S. M. (2005). Model uncertainty and the management of a system of infrastructure facilities. Transportation Research Part C Emerging Technologies. https://doi.org/10.1016/j.trc.2006.02.001
Chu, J. C., & Chen, Y.-J. (2012). Optimal threshold-based network-level transportation infrastructure lifecycle management with heterogeneous maintenance actions. Transportation Research Part B Methodological, 46, 1123–1143. https://doi.org/10.1016/j.trb.2012.05.002
Sathaye, N., & Madanat, S. (2012). A bottom-up optimal pavement resurfacing solution approach for large-scale networks. Transportation Research Part B Methodological. https://doi.org/10.1016/j.trb.2011.12.001
Donev, V., & Hoffmann, M. (2020). Optimisation of pavement maintenance and rehabilitation activities, timing and work zones for short survey sections and multiple distress types. International Journal of Pavement Engineering, 21, 583–607. https://doi.org/10.1080/10298436.2018.1502433
Amarnath, M. S., Raji, A. K., & Rejani, V. U. (2011). Rural road connectivity using CLUSTAL algorithm. Indian Highways, 39, 43–54
Zhang, W., & Durango-Cohen, P. L. (2014). Explaining heterogeneity in pavement deterioration: clusterwise linear regression model. Journal of Infrastructure Systems. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000182
Khadka, M., Paz, A., Arteaga, C., & Hale, D. K. (2018). Simultaneous generation of optimum pavement clusters and associated performance models. Mathematical Problems in Engineering, 2018, 36–37. https://doi.org/10.1155/2018/2159865
Tartibu, L. K., Sun, B., & Kaunda, M. A. E. (2015). Multi-objective optimization of the stack of a thermoacoustic engine using GAMS. Applied Soft Computing Journal. https://doi.org/10.1016/j.asoc.2014.11.055
Amosa, M. K., & Majozi, T. (2016). GAMS supported optimization and predictability study of a multi-objective adsorption process with conflicting regions of optimal operating conditions. Computers and Chemical Engineering. https://doi.org/10.1016/j.compchemeng.2016.08.014
Karthik, K. R., Rejani, V. U., Sunitha, V., Mathew, S., & Veeraragavan, A. (2016). Urban pavement maintenance management system for Tiruchirapalli city. In: 8th International conference on maintenance and rehabilitation of pavements, MAIREPAV 2016, pp. 630–639. Research Publishing Services. https://doi.org/10.3850/978-981-11-0449-7-109-cd
González, J. A. (2002). Probabilistic production costing modeled with AMPL. IEEE Transactions on Power Systems. https://doi.org/10.1109/TPWRS.2002.1007893
Liu, B., & Jin, N. (2015). An application of lingo software to solve dynamic programming problem in the field of environmental protection. In: Proceedings of 2015 IEEE advanced information technology, electronic and automation control conference, IAEAC 2015. https://doi.org/10.1109/IAEAC.2015.7428619
Lopez, A. F. J., Pelayo, M. C. P., & Forero, A. R. (2016). Teaching image processing in engineering using Python. Revista Iberoamericana de Tecnologias Del Aprendizaje. https://doi.org/10.1109/RITA.2016.2589479
Chuan, W., Lei, Y., & Jianguo, Z. (2014). Study on optimization of radiological worker allocation problem based on nonlinear programming function-fmincon. In: 2014 IEEE international conference on mechatronics and automation, IEEE, Tianjin, pp. 1073–1078. https://doi.org/10.1109/ICMA.2014.6885847
Castro, M. S., Saraiva, J. T., & Sousa, J. C. (2016). Application of the Matlab® Linprog function to plan the short term operation of hydro stations considered as price makers. In: International conference on the European Energy Market, EEM. https://doi.org/10.1109/EEM.2016.7521186
Benhamida, F., Ziane, I., Souag, S., Salhi, Y., & Dehiba, B. (2013). A quadratic programming optimization for dynamic economic load dispatch: Comparison with GAMS. In: 2013 3rd International conference on systems and control, ICSC 2013. https://doi.org/10.1109/ICoSC.2013.6750926
Ameri, M., Jarrahi, A., Haddadi, F., Mirabimoghaddam, M. H., & Weber, G. W. (2019). A two-stage stochastic model for maintenance and rehabilitation planning of pavements. Mathematical Problems in Engineering. https://doi.org/10.1155/2019/3971791
Pavement Maintenance Management. Technical Manual TM 5-623, Department of the Army, Washington DC, USA, 1982
IRC:82. (1982). Code of practice for maintenance of bituminous surfaces of highways, Journal of Indian Roads Congress, New Delhi, India, 1982
Rejani, V. U., Sunitha, V., & Mathew, S. (2021). Upgradation of pavement deterioration models for urban roads by non-hierarchical clustering. International Journal of Pavement Research and Technology, 14, 243–251. https://doi.org/10.1007/s42947-020-0105-1
Rejani, V. U., Sunitha, V., & Mathew, S. (2016). Urban pavement maintenance management system for Tiruchirappalli city. In: Proceeding of the conference on transportation systems engineering and management, Bengaluru, pp. 464–473
Acknowledgements
The authors are thankful to the Centre of Excellence in Urban Transport, Dept. of Civil Engineering, IIT Madras, Ministry of Urban Development, Government of India and Centre of Excellence in Transportation Engineering, Dept. of Civil Engineering, NIT, Trichy for sponsoring this research endeavour.
Funding
Supported by Centre of Excellence in Urban Transport, Dept. of Civil Engineering, IIT Madras and Ministry of Urban Development, Government of India Order No: F.ICSR/PA-8-CIE-157/2010/4772 dt 07/12/2010.
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Rejani, V.U., Sunitha, V., Mathew, S. et al. A Network Level Pavement Maintenance Optimisation Approach Deploying GAMS. Int. J. Pavement Res. Technol. 15, 863–875 (2022). https://doi.org/10.1007/s42947-021-00058-6
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DOI: https://doi.org/10.1007/s42947-021-00058-6