A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction

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We present a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. The proposed bottom-up approach adopts an augmented condition state to account for the history-dependent properties of pavement deterioration, and solves for steady-state policies for an infinite horizon. Genetic algorithms (GAs) are implemented in the system-level optimization based on segment-specific optimization results. The complexity of the proposed algorithm is polynomial in the size of the system and the policy-related parameters. We provide graphical presentations of the optimal solutions for various budget situations. As a case study, a subset of California's highway system is analyzed. The case study results demonstrate the economic benefit of a combined rehabilitation and reconstruction budget compared to separate budgets. (C) 2015 Elsevier Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2015-08
Language
English
Article Type
Article
Citation

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, v.78, pp.106 - 122

ISSN
0191-2615
DOI
10.1016/j.trb.2015.05.001
URI
http://hdl.handle.net/10203/251541
Appears in Collection
GT-Journal Papers(저널논문)
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