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

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  • Lee, Jinwoo
  • Madanat, Samer

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.

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  • Lee, Jinwoo & Madanat, Samer, 2015. "A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 106-122.
    • Handle: RePEc:eee:transb:v:78:y:2015:i:c:p:106-122
    DOI: 10.1016/j.trb.2015.05.001
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    References listed on IDEAS

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    1. Li, Yuwei & Madanat, Samer, 2002. "A steady-state solution for the optimal pavement resurfacing problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(6), pages 525-535, July.
    2. Sathaye, Nakul & Madanat, Samer, 2011. "A bottom-up solution for the multi-facility optimal pavement resurfacing problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1004-1017, August.
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    Cited by:

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    3. Zhang, Le & Fu, Liangliang & Gu, Weihua & Ouyang, Yanfeng & Hu, Yaohua, 2017. "A general iterative approach for the system-level joint optimization of pavement maintenance, rehabilitation, and reconstruction planning," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 378-400.
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    5. Chu, James C. & Huang, Kai-Hsiang, 2018. "Mathematical programming framework for modeling and comparing network-level pavement maintenance strategies," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 1-25.
    6. Lee, Jinwoo & Madanat, Samer & Reger, Darren, 2016. "Pavement systems reconstruction and resurfacing policies for minimization of life‐cycle costs under greenhouse gas emissions constraints," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 618-630.

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