Maintenance and Repair Decision Making for Infrastructure Facilities without a Deterioration Model
Publication: Journal of Infrastructure Systems
Volume 10, Issue 1
Abstract
In the existing approach to maintenance and repair decision making for infrastructure facilities, policy evaluation and policy selection are performed under the assumption that a perfect facility deterioration model is available. The writer formulates the problem of developing maintenance and repair policies as a reinforcement learning problem in order to address this limitation. The writer explains the agency-facility interaction considered in reinforcement learning and discuss the probing-optimizing dichotomy that exists in the process of performing policy evaluation and policy selection. Then, temporal-difference learning methods are described as an approach that can be used to address maintenance and repair decision making. Finally, the results of a simulation study are presented where it is shown that the proposed approach can be used for decision making in situations where complete and correct deterioration models are not (yet) available.
Get full access to this article
View all available purchase options and get full access to this article.
References
Bellman, R. E.(1955). “Equipment replacement policy.” J. Soc. Ind. Appl. Math., 8(3), 133–146.
Bertsekas, D. (1995). Dynamic programming and optimal control, Athena Scientific, Belimont, Mass.
Carnahan, J., Davis, W., Shahin, M., Keane, P., and Wu, M.(1987). “Optimal maintenance decisions for pavement management.” J. Transp. Eng., 113(5), 554–572.
Dreyfus, S.(1960). “A generalized equipment replacement study.” J. Soc. Ind. Appl. Math., 8(3), 425–435.
Durango, P. (2002). “Adaptive optimization models for infrastructure management.” PhD thesis, Univ. of California, Berkeley, Berkeley, Calif.
Durango, P., and Madanat, S.(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, 763–778.
Fernandez, J. (1979). “Optimal dynamic investment policies for public facilities: The transportation case.” PhD thesis, Massachusetts Institute of Technology, Cambridge, Mass.
Gendreau, M., and Soriano, P.(1998). “Airport pavement management systems: An appraisal of existing methodologies.” Transp. Res., Part A: Policy Pract., 32(3), 197–214.
Golabi, K., Kulkarni, R., and Way, G.(1982). “A statewide pavement management system.” Interfaces, 12(6), 5–21.
Madanat, S., and Ben-Akiva, M.(1994). “Optimal inspection and repair policies for infrastructure facilities.” Transp. Sci., 28(1), 55–61.
Ross, S. (1992). Applied probability models with optimization applications, Dover, New York.
Sutton, R., and Barto, A. (1998). Reinforcement learning: An introduction, MIT Press, Cambridge, Mass.
Terborgh, G. (1949). Dynamic equipment replacement policy, McGraw-Hill, New York.
Information & Authors
Information
Published In
Copyright
Copyright © 2004 American Society of Civil Engineers.
History
Received: Oct 25, 2002
Accepted: Jul 29, 2003
Published online: Feb 19, 2004
Published in print: Mar 2004
Authors
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.