Abstract
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.
Original language | English (US) |
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Pages (from-to) | 106-122 |
Number of pages | 17 |
Journal | Transportation Research Part B: Methodological |
Volume | 78 |
DOIs | |
State | Published - Aug 1 2015 |
Keywords
- Bottom-up optimization
- History-dependent deterioration
- Multiple constraints
- Pavement reconstruction
- Pavement rehabilitation
ASJC Scopus subject areas
- Civil and Structural Engineering
- Transportation