Optimal reconstruction periods for stochastically deteriorating infrastructures

Computer-Aided Civil and Infrastructure Engineering

Volumn 22, Issue 6, 2007, Pages 389-399

  Pasupathy, Raghu ^a   Labi, Samuel ^b   Sinha, Kumares C ^b  

^a Virginia Polytechnic Institute and State University   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COST EFFECTIVENESS; NUMERICAL METHODS; OPTIMIZATION; RANDOM PROCESSES; RESTORATION;

INFRASTRUCTURE SYSTEM; RECONSTRUCTION PERIODS; STOCHASTIC DETERIORATION PROCESS;

RECONSTRUCTION (STRUCTURAL);

COST EFFECTIVENESS; NUMERICAL METHODS; OPTIMIZATION; RANDOM PROCESSES; RECONSTRUCTION (STRUCTURAL); RESTORATION;

INFRASTRUCTURE; NUMERICAL METHOD; OPTIMIZATION; RECONSTRUCTION; STOCHASTICITY;

EID: 34250345655     PISSN: 10939687     EISSN: 14678667     Source Type: Journal    
DOI: 10.1111/j.1467-8667.2007.00495.x     Document Type: Article

References (25)

1. Aberth, O. (1973), Iteration methods for finding all zeros of a polynomial simultaneously, Math. Computations, 27, 339-344.
2. Archilla, A. R. & Madanat, S. (2000), Development of a pavement rutting model from experimental data, ACSE Journal of Transportation Engineering, 126 (4), 291-299.
3. Billingsley, P. (1995), Probability and Measure, John Wiley & Sons, New York.
4. Boardman, A. E., Greenberg, D. H., Vining, A. R. & Weimer, D. L. (2001), Cost-Benefit Analysis: Concepts and Practice, Prentice Hall, Upper Saddle River, NJ.
5. Chan, P. K., Oppermann, M. C. & Wu, S. (1997), North Carolina's experience in development of pavement performance prediction and modeling, Transportation Research Record, 1592, 80-88.
6. Conte, S. D. & De Boor, C. (1980), Elementary Numerical Analysis: An Algorithmic Approach, McGraw-Hill, New York.
7. Daleiden, J. F., Brent R. J., Killingsworth, B., Owusu-Antwi, E., Darter M. J. & Ahmad, R. (1993), Evaluation of the AASHTO design equations and recommended improvements, in Proceedings of the Transportation Research Board, National Research Council, Washington, D.C.
8. Durango, P. & Madanat, S. (2002), Optimal maintenance and repair policies in infrastructure management under uncertain facility deterioration rates: An adaptive control approach, Transportation Research Part A, 36 (9), 763-778.
9. Federal Highway Administration (1999), Asset Management Primer, Office of Asset Management, U.S. Department of Transportation, Washington, D.C.
10. GASB (1999), GASB statement No. 34: Basic Financial Statements and Management's Discussion and Analysis for State and Local Governments, Governmental Accounting Standards Board, Norwalk, CT.
11. George, K. P., Rajagopal, A. S. & Lim, L. K. (1989), Models for predicting pavement deterioration, Transportation Research Record, 1215, 1-7.
12. Johnson, K. D. & Cation., K. A. (1992), Performance prediction development using three indexes for North Dakota pavement management system, Transportation Research Record, 1344, 22-30.
13. Labi, S. & Sinha, K. C. (2002), The Effectiveness of Maintenance and Its Impact on Capital Expenditures, Final Report. FHWA/IN/JTRP-2003, West Lafayette, IN.
14. Lamptey, G. (2004), Optimal scheduling of pavement preventive maintenance, M.S. thesis, Purdue University, West Lafayette, IN.
15. Li, Y. & Madanat, S. (2002), A steady-state solution for the optimal pavement resurfacing problem, Transportation Research Part A, 36, 525-535.
16. Madanat, S. & Ben-Akiva, M. (1994), Optimal inspection and repair policies for infrastructure facilities, Transportation Science, 28 (1), 55-61.
17. Markow, M. & Balta, W. (1985), Optimal rehabilitation frequencies for highway pavements, Transportation Research Record, 1035, 31-43.
18. Pasupathy, R. (2006), On choosing parameters in retrospective-approximation algorithms for simulation-optimization, in Proceedings of the 2006 Winter Simulation Conference, ed. L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, 208-215.
19. Pasupathy, R. & Henderson, S. G. (2006), A testbed of simulation-optimization problems, in Proceedings of the 2006 Winter Simulation Conference, ed. L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, 255-263.
20. Patterson, W. D. O. & Attoh-Okine, B. (1992), Summary models of paved road deterioration based on HDM-III, Transportation Research Record, 1344, 99-105.
21. Shapiro, A. (2003), Monte Carlo Sampling Methods, in A. Ruszczynski and A. Shapiro (eds.), Handbook of Stochastic Optimization, Elsevier Science Publishers, Netherlands.
22. Shapiro, A. & Homem-de-Mello, T. (2003), On rate of convergence of Monte Carlo approximations of stochastic programs, SIAM Journal on Optimization, 11, 70-86.
23. Sharaf, E. A., Shahin, M. Y. & Sinha, K. C. (1988), Analysis of the effect of deferring pavement maintenance, Transportation Research Record, 1205, 29-35.
24. Shekaran, A. R. (1997), Solution of Pavement Deterioration Equations by Genetic Algorithms, presented at the 79th Annual Meeting of the Transportation Research Board, Washington, D.C.
25. Tsunokawa, K. & Schofer, J. L. (1994), Trend curve optimal control model for highway pavement maintenance: Case study and evaluation, Transportation Research Part A, 28, 151-166.