Optimal Maintenance and Rehabilitation Policies for Performance-Based Road Maintenance Contracts
Publication: Journal of Performance of Constructed Facilities
Volume 31, Issue 1
Abstract
Performance-based road maintenance contracts (PBRMCs) are an effective mechanism to transfer risk and responsibility of road maintenance activities to the private sector. Proper structuring of performance indicators and the extent of penalties and incentives in the contract has a significant effect on the overall cost and level of service (LOS) provided to the public. This research develops a series of mathematical optimization models and a computational tool that allows road agencies and contractors to better structure the following contractual conditions in a performance-based contract (PBC) for road maintenance: (1) types of performance indicators to be considered; (2) their threshold levels; and (3) the appropriate levels of penalties and incentives. The availability of such models and tools will allow road agencies and contractors that are unfamiliar with PBRMCs to make informed decisions on their approach to contractual risk allocation. A case study of a major highway in Egypt is presented to demonstrate how slight changes in performance thresholds and contractual penalties affect the overall lifecycle costs (LCC) and eventual road performance. The results demonstrate that: (1) small variations in KPI thresholds can have a significant effect on the overall lifecycle costs and eventual contract price; and (2) the addition of penalties and incentives can be an effective mechanism to ensure contractors adhere to performance requirements in PBRMCs.
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References
Adedimila, A., Olutaiwo, A., and Kehinde, O. (2009). “Markovian probabilistic pavement performance prediction models for a developing country.” J. Eng. Appl. Sci., 4(1), 13–26.
Baoshan, H., and Qiao, D. (2009). “Optimizing pavement preventive maintenance treatment applications in Tennessee (phase 1).” Tennessee Dept. of Transportation, Nashville, TN.
Bemanian, S., Polish, P., and Maurer, G. (2005). “Pavement management system based on financial consequence.” Transp. Res. Rec., 1940(1), 32–37.
Chootinan, P., Chen, A., Horrocks, M. R., and Bolling, D. (2006). “A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach.” Transp. Res. Part A: Policy Pract., 40(9), 725–743.
De la Garza, J. M., Pinero, J. C., and Ozbek, M. E. (2009). “A framework for monitoring performance-based road maintenance contracts.” Proc., Associated Schools of Construction 45th Annual Int. Conf., Gainesville, FL, 433–441.
Durango, P. L., and Madanat, S. M. (2002). “Optimal maintenance and repair policies in infrastructure management under uncertain facility deterioration rates: An adaptive control approach.” Transp. Res. Part A: Policy Pract., 36(9), 763–778.
El-Assaly, A., Ariaratnam, S., and Hempsey, L. (2002). “Development of deterioration models for the primary highway network in Alberta, Canada.” Annual Conf. of the Canadian Society for Civil Engineering, Canadian Society for Civil Engineering (CSCE), Montréal, QC.
Farashah, K. (2012). “Development practices for municipal pavement management systems application.” Masters thesis, Univ. of Waterloo, Toronto.
Ferreira, A., Picado-Santos, L. D., Wu, Z., and Flintsch, G. (2011). “Selection of pavement performance models for use in the Portuguese PMS.” Int. J. Pavement Eng., 12(1), 87–97.
George, K. (2000). “MDOT pavement management system—Prediction models and feedback systems.” Mississippi Dept. of Transportation, Jackson, MS.
Hudson, W. R., Haas, R., and Pedigo, R. D. (1979). “Pavement management system development.”, Washington, DC.
Hudson, W. R., Haas, R., and Uddin, W. (1997). “Infrastructure management: Integrating design, construction, maintenance.” Rehabilitation and renovation, McGraw-Hill, New York.
Javed, F. (2010). “Integrated prioritization and optimization approach for pavement management.” Doctoral dissertation, National Univ. of Singapore, Singapore.
Jeerangsuwan, T., Said, H., Kandil, A., and Ukkusuri, S. (2013). “Financial evaluation for toll road projects considering traffic volume and serviceability interactions.” J. Infrastruct. Syst., 04014012.
Jeong, J., Lim, J., Suh, Y., and Nam, J. (2012). “Development of performance criteria for Korean pavement warranty specification.” J. Perform. Constr. Facil., 402–411.
Kandil, A., and El-Rayes, K. (2006). “Parallel genetic algorithms for optimizing resource utilization in large-scale construction projects.” J. Constr. Eng. Manage., 491–498.
Lee, C., and Kwak, N. (1999). “Information resource planning for a health-care system using an AHP-based goal programming method.” J. Oper. Res. Soc., 50(12), 1191–1198.
Liu, F., and Wang, K. C. (1996). “Pavement performance-oriented network optimization system.” Transp. Res. Rec., 1524(1), 86–93.
Mahoney, J. (1990). Introduction to prediction models and performance curves, Federal Highway Adminstration (FHWA), Washington, DC.
Martin, L. (2003). “Making performance-based contracting perform: What the federal government can learn from the state and local governments.” The procurement revolution, Rowman and Littlefield, New York, 87–125.
Mubaraki, M. (2010). “Predicting deterioration for the Saudi Arabia Urban road network.” Doctoral dissertation, Univ. of Nottingham, U.K.
OECD (Organization for Economic Co-operation and Development). (2001). Performance indicators for the road sector—Summary of the field tests, Paris, France.
Osman, H. (2005). “Risk-based life-cycle cost analysis of privatized infrastructure.” Transp. Res. Rec., 1924(1), 192–196.
Osman, H., Georgy, M. E., and Ibrahim, M. E. (2003). “A hybrid CAD-based construction site layout planning system using genetic algorithms.” Autom. Constr., 12(6), 749–764.
Oyedele, L. O. (2013). “Avoiding performance failure payment deductions in PFI/PPP projects: Model of critical success factors.” J. Perform. Constr. Facil., 283–294.
Piñero, J. C. (2003). “A framework for monitoring performance-based road maintenance.” Doctoral dissertation, Virginia Polytechnic Institute and State Univ., Blacksburg, VA.
Rashedi, R., and Hegazy, T. (2013). “Capital renewal optimization in large-scale infrastructure networks: GA versus advanced mathematical tools.” J. Struct. Infrastruct. Eng., 11(3), 253–262.
Robinson, C., Beg, M. A., Dossey, T., and Hudson, W. R. (1996). “Distress prediction models for rigid pavements for Texas pavement management information system.” Transp. Res. Rec., 1524(1), 145–151.
Schniederjans, M. (1995). Goal programming: Methodology and applications: Methodology and applications, Springer Science and Business Media, New York.
Segal, G. F., Moore, A. T., and McCarthy, S. (2003). Contracting for road and highway maintenance, Reason Public Policy Institute, London.
Shahin, A. A., and Salem, O. M. (2004). “Using genetic algorithms in solving the one-dimensional cutting stock problem in the construction industry.” Constr. J. Civ. Eng., 31(2), 321–332.
Stankevich, N., Qureshi, N., and Queiroz, C. (2005). “Performance-based contracting for preservation and improvement of road assets.”.
Surendrakumar, K., Prashant, N., and Mayuresh, P. (2013). “Application of Markovian probabilistic process to develop a decision support system for pavement maintenance management.” Int. J. Sci. Technol. Res., 2(8), 295–303.
Tack, J. N., and Chou, E. J. (2002). “Multiyear pavement repair scheduling optimization by preconstrained genetic algorithm.” Transp. Res. Rec., 1816(1), 3–8.
Tjan, A., Ciumbuleuit, J., and Pitaloka, D. (2005). “Future prediction of pavement condition using markov probability transition matrix.” Proc., Eastern Asia Society for Transportation Studies, Vol. 5, Japan Science and Technology Information Aggregator, Electronic, Tokyo, Japan, 772–782.
Zietlow, G. (2004). Implementing performance-based road management and maintenance contracts in developing countries—An instrument of German technical cooperation, German Development Cooperation (GTZ), Eschborn, Germany.
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Published In
Journal of Performance of Constructed Facilities
Volume 31 • Issue 1 • February 2017
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Apr 22, 2015
Accepted: Apr 11, 2016
Published online: Jul 11, 2016
Discussion open until: Dec 11, 2016
Published in print: Feb 1, 2017
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