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

Jinwoo Lee, Samer Madanat

Research output: Contribution to journalArticlepeer-review


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 languageEnglish (US)
Pages (from-to)106-122
Number of pages17
JournalTransportation Research Part B: Methodological
StatePublished - Aug 1 2015


  • Bottom-up optimization
  • History-dependent deterioration
  • Multiple constraints
  • Pavement reconstruction
  • Pavement rehabilitation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation


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