Technical Papers
Nov 13, 2018

Impact of Multiple Highway Funding Categories and Project Eligibility Restrictions on Pavement Performance

Publication: Journal of Infrastructure Systems
Volume 25, Issue 1

Abstract

In maintenance and rehabilitation (M&R) programming, most budget allocation models in literature often assume one principal budget that can be used for funding all the different projects undertaken by the decision-making entity. For most agencies, this is rarely the case. This study explores the impact of formulating the M&R budget allocation problem with multiple funding categories (or budgets) having stringent project eligibility constraints. For state highway agencies (SHAs), there are often several federal, state, and local funding sources for highway projects. There are also agency norms and regulations that restrain the eligible projects under each funding category. This study presents an integer–linear programming model that accounts for funding restrictions in M&R budgets to assess changes in network performance and M&R decisions for pavement assets. The model is implemented in a numerical case study representing a subset network consisting of 500 pavement sections. Findings from this study suggest that the projected performance of the M&R program is overestimated when there is the assumption of one “central” budget with no project eligibility constraints. This may lead to an increase in unplanned expenditures toward reactive M&R projects to meet performance targets. Furthermore, the findings also suggest that increasingly restrictive budgets lead to a lower network performance for the same aggregate budget. The sensitivity analyses conducted confirm that the results obtained are robust against variations in key input variables used in the model. These findings contribute to ongoing efforts toward incorporating pragmatic constraints in optimization models to enhance their utility for effective decision making.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The research work presented in this paper was funded by the Fort Worth District of TxDOT. Furthermore, the authors would also like to thank agency staff at the district for making data available and providing useful insights concerning the complex nature of M&R programming. The opinions and findings in this study are those of the authors and do not necessarily reflect the views of TxDOT.

References

Abaza, K. A., and S. A. Ashur. 2009. “Optimum microscopic pavement management model using constrained integer linear programming.” Int. J. Pavement Eng. 10 (3): 149–160. https://doi.org/10.1080/10298430802068907.
Ahmed, S., P. Vedagiri, and K. V. Krishna Rao. 2017. “Prioritization of pavement maintenance sections using objective based analytic hierarchy process.” Int. J. Pavement Res. Technol. 10 (2): 158–170. https://doi.org/10.1016/j.ijprt.2017.01.001.
Almalki, A., W. Rasdorf, C. Pilson, J. Arnold, and M. Whitley. 2016. “An infrastructure maintenance funding framework for a transportation agency.” In Proc., Construction Research Congress 2016, 1435–1444. Reston, VA: ASCE.
Anani, S. B., and S. M. Madanat. 2010. “Estimation of highway maintenance marginal cost under multiple maintenance activities.” J. Transp. Eng. 136 (10): 863–870. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000150.
ASCE. 2017. 2017 Infrastructure Report Card. Reston, VA: ASCE.
Boyles, S. D., Z. Zhang, and S. T. Waller. 2010. “Optimal maintenance and repair policies under nonlinear preferences.” J. Infrastruct. Syst. 16 (1): 11–20. https://doi.org/10.1061/(ASCE)1076-0342(2010)16:1(11).
Bussieck, M. R., and S. Vigerske. 2010. “MINLP solver software.” In Wiley encyclopedia of operations research and management science. New York: Wiley.
California Department of Transportation. 2015. “2015 ten-year state highway operation and protection program plan (SHOPP Plan).” Accessed December 17, 2017. http://www.dot.ca.gov/hq/transprog/SHOPP/prior_shopp_documents/10yr_SHOPP_Plan/2015_Ten_Year_SHOPP_Plan_Final.pdf.
Cambridge Systematics. 2009. An asset-management framework for the interstate highway system. Washington, DC: Transportation Research Board.
Chen, L. X., A. A. Chowdhury, C. M. Loulakis, M. A. Ownes, H. Thorisson, E. B. Connelly, C. J. Tucker, and J. H. Lambert. 2015. “Visualization of large data sets for project planning and prioritization on transportation corridors.” In Systems and Information Engineering Design Symp. (SIEDS), 1–6. Piscataway, NJ: IEEE.
Chen, X., H. Zhu, Q. Dong, and B. Huang. 2017. “Optimal thresholds for pavement preventive maintenance treatments using LTPP data.” J. Transp. Eng. Part A: Syst. 143 (6): 04017018. https://doi.org/10.1061/JTEPBS.0000044.
Chi, S., J. Hwang, M. Arellano, Z. Zhang, and M. Murphy. 2013. “Development of network-level project screening methods supporting the 4-year pavement management plan in Texas.” J. Manage. Eng. 29 (4): 482–494. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000158.
Chootinan, P., A. Chen, M. R. Horrocks, and D. Bolling. 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. https://doi.org/10.1016/j.tra.2005.12.003.
Chu, J. C., and K.-H. Huang. 2018. “Mathematical programming framework for modeling and comparing network-level pavement maintenance strategies.” Transp. Res. Part B: Methodol. 109: 1–25. https://doi.org/10.1016/j.trb.2018.01.005.
Dekker, R. 1996. “Applications of maintenance optimization models: A review and analysis.” Reliab. Eng. Syst. Saf. 51 (3): 229–240. https://doi.org/10.1016/0951-8320(95)00076-3.
De La Garza, J. M., S. Akyildiz, D. R. Bish, and D. A. Krueger. 2011. “Network-level optimization of pavement maintenance renewal strategies.” Adv. Eng. Inf. 25 (4): 699–712. https://doi.org/10.1016/j.aei.2011.08.002.
D’Ignazio, J., S. Rhodes, and C. Secrest. 2015. The role of planning in a 21st century State Department of Transportation—Supporting strategic decisionmaking. Washington, DC: Transportation Research Board.
Dong, Q., B. Huang, S. H. Richards, and X. Yan. 2013. “Cost-effectiveness analyses of maintenance treatments for low- and moderate-traffic asphalt pavements in Tennessee.” J. Transp. Eng. 139 (8): 797–803. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000556.
Duncan, C., and K. Schroeckenthaler. 2017. Resource allocation of available funding to programs of work. NCHRP Synthesis 510. Washington, DC: Transportation Research Board.
Farhan, J., and T. F. Fwa. 2012. “Incorporating priority preferences into pavement maintenance programming.” J. Transp. Eng. 138 (6): 714–722. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000372.
France-Mensah, J., and W. J. O’Brien. 2018. “Budget allocation models for pavement maintenance and rehabilitation: Comparative case study.” J. Manage. Eng. 34 (2): 05018002. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000599.
France-Mensah, J., W. J. O’Brien, N. Khwaja, and L. C. Bussell. 2017a. “GIS-based visualization of integrated highway maintenance and construction planning: A case study of Fort Worth, Texas.” Visual. Eng. 5 (1): 7. https://doi.org/10.1186/s40327-017-0046-1.
France-Mensah, J., B. Sankaran, and W. J. O’Brien. 2017b. “Integrating highway projects data in GIS for maintenance and rehabilitation planning: Applications, challenges, and recommendations.” In Computing Civil Engineering, 343–351. Reston, VA: ASCE.
Fwa, T. F., and J. Farhan. 2012. “Optimal multiasset maintenance budget allocation in highway asset management.” J. Transp. Eng. 138 (10): 1179–1187. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000414.
Gao, L., and Z. Zhang. 2008. “Robust optimization for managing pavement maintenance and rehabilitation.” Transp. Res. Rec. 2084 (1): 55–61. https://doi.org/10.3141/2084-07.
Gao, L., and Z. Zhang. 2009. “Approximate dynamic programming approach to network-level budget planning and allocation for pavement infrastructure.” In Transportation Research Board 88th Annual Meeting. Washington, DC: Transportation Research Board.
Gharaibeh, N. G., P. Narciso, Y. Cha, J. Oh, J. R. Menendez, S. Dessouky, and A. Wimsatt. 2014. A methodology to support the development of 4-year pavement management plan. College Station, TX: Texas A&M Transportation Institute.
Harrison, F. 2005. Analytical tools for asset management. NCHRP Rep. 545. Washington, DC: Transportation Research Board.
Hong, F., E. Perrone, M. Mikhail, and A. Eltahan. 2017.“ Planning pavement maintenance and rehabilitation projects in the new pavement management system in Texas.” In Proc., 96th Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Kuhn, K. D. 2010. “Network-level infrastructure management using approximate dynamic programming.” J. Infrastruct. Syst. 16 (2): 103–111. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000019.
Kulkarni, R. B., D. Miller, R. M. Ingram, C.-W. Wong, and J. Lorenz. 2004. “Need-based project prioritization: Alternative to cost-benefit analysis.” J. Transp. Eng. 130 (2): 150–158. https://doi.org/10.1061/(ASCE)0733-947X(2004)130:2(150).
Labi, S., and K. C. Sinha. 2005. “Life-cycle evaluation of flexible pavement preventive maintenance.” J. Transp. Eng. 131 (10): 744–751. https://doi.org/10.1061/(ASCE)0733-947X(2005)131:10(744).
Lamptey, G., S. Labi, and Z. Li. 2008. “Decision support for optimal scheduling of highway pavement preventive maintenance within resurfacing cycle.” Decis. Support Syst. 46 (1): 376–387. https://doi.org/10.1016/j.dss.2008.07.004.
Lee, J., and S. Madanat. 2017. “Optimal policies for greenhouse gas emission minimization under multiple agency budget constraints in pavement management.” Transp. Res. Part D: Transp. Environ. 55: 39–50. https://doi.org/10.1016/j.trd.2017.06.009.
Li, Z., and S. Madanu. 2009. “Highway project level life-cycle benefit/cost analysis under certainty, risk, and uncertainty: Methodology with case study.” J. Transp. Eng. 135 (8): 516–526. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000012.
Liu, W., S. Jaipuria, M. R. Murphy, and Z. Zhang. 2012. A four-year pavement management plan (FY 2011–FY 2014). Austin, TX: Center for Transportation Research.
Medury, A., and S. Madanat. 2013. “Incorporating network considerations into pavement management systems: A case for approximate dynamic programming.” Transp. Res. Part C: Emerging Technol. 33: 134–150. https://doi.org/10.1016/j.trc.2013.03.003.
Medury, A., and S. Madanat. 2014. “Simultaneous network optimization approach for pavement management systems.” J. Infrastruct. Syst. 20 (3): 04014010. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000149.
Menendez, J., S. Siabil, P. Narciso, and N. Gharaibeh. 2013. “Prioritizing infrastructure maintenance and rehabilitation activities under various budgetary scenarios.” Transp. Res. Rec. 2361: 56–62. https://doi.org/10.3141/2361-07.
Menendez, J. R., and N. G. Gharaibeh. 2017. “Incorporating risk and uncertainty into infrastructure asset management plans for pavement networks.” J. Infrastruct. Syst. 23 (4): 04017019. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000379.
Mild, P., and A. Salo. 2009. “Combining a multiattribute value function with an optimization model: An application to dynamic resource allocation for infrastructure maintenance.” Decis. Anal. 6 (3): 139–152. https://doi.org/10.1287/deca.1090.0143.
Mitchell, J. E. 2002. “Branch-and-cut algorithms for combinatorial optimization problems.” In Handbook of applied optimization, 65–77. Troy, NY: Rensselaer Polytechnic Institute.
Morcous, G., and Z. Lounis. 2005. “Maintenance optimization of infrastructure networks using genetic algorithms.” Autom. Constr. 14 (1): 129–142. https://doi.org/10.1016/j.autcon.2004.08.014.
Ng, M., Z. Zhang, and S. T. Waller. 2011. “The price of uncertainty in pavement infrastructure management planning: An integer programming approach.” Transp. Res. Part C: Emerging Technol. 19 (6): 1326–1338. https://doi.org/10.1016/j.trc.2011.03.003.
O’Brien, W. J., P. Gau, C. Schmeits, J. Goyat, and N. Khwaja. 2012. “Benefits of three- and four-dimensional computer-aided design model applications for review of constructability.” Transp. Res. Rec. 2268: 18–25. https://doi.org/10.3141/2268-03.
Porras-Alvarado, J. D. 2016. “A methodological framework for cross-asset resource allocations to support infrastructure management.” Ph.D. dissertation, Dept. of Civil, Architectural, and Environmental Engineering, Univ. of Texas at Austin.
Porras-Alvarado, J. D., Z. Han, and Z. Zhang. 2015. “A fair division approach to performance-based cross-asset resource allocation.” In Proc., 9th Int. Conf. on Managing Pavement Assets. Alexandria, VA: Virginia Tech Transportation Institute.
Porras-Alvarado, J. D., M. R. Murphy, H. Wu, Z. Han, Z. Zhang, and M. Arellano. 2017. “Analytical hierarchy process to improve project prioritization in the Austin district, Texas.” Transp. Res. Rec. 2613: 29–36. https://doi.org/10.3141/2613-04.
Saha, P., and K. Ksaibati. 2015. “A risk-based optimization methodology for managing county paved roads.” In Proc., 94th Transportation Research Board Annual Meeting 2015. Washington, DC: Transportation Research Board.
Sahin, H., P. Narciso, and N. Hariharan. 2014. “Developing a five-year maintenance and rehabilitation (M&R) plan for HMA and concrete pavement networks.” APCBEE Procedia 9: 230–234. https://doi.org/10.1016/j.apcbee.2014.01.041.
Sankaran, B., W. J. O’Brien, P. M. Goodrum, N. Khwaja, F. L. Leite, and J. Johnson. 2016. “Civil integrated management for highway infrastructure.” Transp. Res. Rec. 2573: 10–17. https://doi.org/10.3141/2573-02.
Sathaye, N., and S. Madanat. 2012. “A bottom-up optimal pavement resurfacing solution approach for large-scale networks.” Transp. Res. Part B: Methodol. 46 (4): 520–528. https://doi.org/10.1016/j.trb.2011.12.001.
Seyedshohadaie, S. R., I. Damnjanovic, and S. Butenko. 2010. “Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks.” Transp. Res. Part A: Policy Pract. 44 (4): 236–248. https://doi.org/10.1016/j.tra.2010.01.005.
Shah, Y. U., S. S. Jain, and M. Parida. 2012. “Evaluation of prioritization methods for effective pavement maintenance of urban roads.” Int. J. Pavement Eng. 15 (3): 238–250. https://doi.org/10.1080/10298436.2012.657798.
Shoghli, O., and J. M. De La Garza. 2016. “A multi-objective decision-making approach for the sustainable maintenance of roadways.” In Proc., Construction Research Congress 2016, 1424–1434. Reston, VA: ASCE.
Small, K. A., C. Winston, and C. A. Evans. 2012. Road work: A new highway pricing and investment policy. Washington, DC: Brookings Institution Press.
Tayebi, N. R., F. M. Nejad, and M. Mola. 2014. “Comparison between GA and PSO in analyzing pavement management activities.” J. Transp. Eng. 140 (1): 99–104. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000590.
Terzi, S., and S. Serin. 2014. “Planning maintenance works on pavements through ant colony optimization.” Neural Comput. Appl. 25 (1): 143–153. https://doi.org/10.1007/s00521-013-1456-1.
Torres-Machí, C., A. Chamorro, C. Videla, E. Pellicer, and V. Yepes. 2014. “An iterative approach for the optimization of pavement maintenance management at the network level.” Sci. World J. 2014: 1–11. https://doi.org/10.1155/2014/524329.
Torres-Machí, C., E. Pellicer, V. Yepes, and A. Chamorro. 2017. “Towards a sustainable optimization of pavement maintenance programs under budgetary restrictions.” J. Cleaner Prod. 148: 90–102. https://doi.org/10.1016/j.jclepro.2017.01.100.
Tsunokawa, K., D. Van Hiep, and R. Ul-Islam. 2006. “True optimization of pavement maintenance options with what-if models.” Comput.-Aided Civ. Infrastruct. Eng. 21 (3): 193–204. https://doi.org/10.1111/j.1467-8667.2006.00427.x.
TxDOT (Texas Department of Transportation). 2014. Condition of Texas pavements: PMIS annual report FY 2011–2014. Austin, TX: TxDOT.
Van Hiep, D., and K. Tsunokawa. 2005. “Optimal maintenance strategies for bituminous pavements: A case study in Vietnam using HDM-4 with gradient methods.” J. Eastern Asia Soc. Transp. Stud. 6: 1123–1136. https://doi.org/10.11175/easts.6.1123.
Wang, F., Z. Zhang, and R. Machemehl. 2003. “Decision-making problem for managing pavement maintenance and rehabilitation projects.” Transp. Res. Rec. 1853: 21–28. https://doi.org/10.3141/1853-03.
Wiegmann, J., and B. Yelchuru. 2012. Resource allocation logic framework to meet highway asset preservation. Washington, DC: Transportation Research Board.
Wu, Z., G. Flintsch, A. Ferreira, and L. Picado-Santos. 2012. “Framework for multiobjective optimization of physical highway assets investments.” J. Transp. Eng. 138 (12): 1411–1421. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000458.
Wu, Z., and G. W. Flintsch. 2009. “Pavement preservation optimization considering multiple objectives and budget variability.” J. Transp. Eng. 135 (5): 305–315. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000006.
Yang, C., R. Remenyte-Prescott, and J. D. Andrews. 2015. “Pavement maintenance scheduling using genetic algorithms.” Int. J. Performability Eng. 11 (2): 135–152.
Zhang, L., L. Fu, W. Gu, Y. Ouyang, and Y. Hu. 2017. “A general iterative approach for the system-level joint optimization of pavement maintenance, rehabilitation, and reconstruction planning.” Transp. Res. Part B: Methodol. 105: 378–400. https://doi.org/10.1016/j.trb.2017.09.014.

Information & Authors

Information

Published In

Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 25Issue 1March 2019

History

Received: Jan 6, 2018
Accepted: Jul 19, 2018
Published online: Nov 13, 2018
Published in print: Mar 1, 2019
Discussion open until: Apr 13, 2019

Permissions

Request permissions for this article.

Authors

Affiliations

Jojo France-Mensah, S.M.ASCE [email protected]
Ph.D. Candidate, Dept. of Civil, Architectural, and Environmental Engineering, Univ. of Texas at Austin, 301 E. Dean Keeton St., ECJ 5.412, Austin, TX 78712 (corresponding author). Email: [email protected]
William J. O’Brien, Ph.D., M.ASCE [email protected]
P.E.
Professor, Dept. of Civil, Architectural, and Environmental Engineering, Univ. of Texas at Austin, 301 E. Dean Keeton St., ECJ 5.412, Austin, TX 78712. Email: [email protected]
Nabeel Khwaja [email protected]
P.E.
Assistant Director, Center for Transportation Research, Univ. of Texas at Austin, 1616 Guadalupe, Suite 4.202, Austin, TX 78701. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share