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Optimized pavement structures via multi-objective optimization using genetic algorithm and highway development and management model four (case study: Iran low-volume roads)

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Abstract

Pavement management and optimization tools at the project level provide designers and decision-makers with an optimal and sustainable solution. This research aimed to optimize pavement-designed sections by employing the multi-objective optimization model (MOOM) and the Highway Development and Management Model Four (HDM-4). The study analyzed 14 distinct designs of low-volume road (LVR) asphalt pavement structures across four climate zones, considering five types of subgrades and four types of traffic volume. Based on the analysis results, it is important to note that, although the selected pavements using MOOM and HDM-4 had lower discounted costs compared to the designed pavements (with reductions of 2.41 and 1.54%, respectively), the optimized pavement structures suggested by these two methods were not identical. In other words, in most cases, the analysis indicated that HDM-4 tended to prefer pavement structures with greater bearing capacity, while MOOM often favored structures with lower bearing capacity. Additionally, the discounted costs of the structures optimized using MOOM were 4.58% less than those of the structures optimized using HDM-4.

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Authors and Affiliations

  1. Department of Civil Engineering, University of Zanjan, Zanjan, Iran

    Alireza Khavandi Khiavi, Farzad Rahimi, Hossein Mohammadi, Ramin Rasouli, Amirhossein Molhemazar & Mohammadreza Asadi

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  1. Alireza Khavandi Khiavi
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  2. Farzad Rahimi
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  3. Hossein Mohammadi
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  4. Ramin Rasouli
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  5. Amirhossein Molhemazar
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  6. Mohammadreza Asadi
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Correspondence to Alireza Khavandi Khiavi.

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Khavandi Khiavi, A., Rahimi, F., Mohammadi, H. et al. Optimized pavement structures via multi-objective optimization using genetic algorithm and highway development and management model four (case study: Iran low-volume roads). Innov. Infrastruct. Solut. 9, 22 (2024). https://doi.org/10.1007/s41062-023-01335-y

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