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Cost-Optimized Approach for Pavement Maintenance Planning of Low Volume Rural Roads: A Case Study in Himalayan Region

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Abstract

Maintenance planning of low volume rural road network is a challenging task due to its large length and importance to the concerned habitation. The proposed methodology is focused on developing a cost-effective maintenance plan for low volume rural Himalayan hill roads by considering the predominant distresses and factors. Maximizing overall network pavement condition rating while minimizing the budget is taken as the objective function in the optimization problem. The maintenance plan is optimized using Knapsack modified Genetic Algorithm technique developed in MATLAB. Validation of the proposed model was done by applying it to a case study of 42 low volume rural hill roads of Hamirpur district of Himachal Pradesh state in India, located in the Himalayan region. Knapsack modified GA makes maintenance planning easier by considering different scenarios of budgetary limitations varying from 0 to 100% of total need. The present model can be very helpful for pavement maintenance planners in developing an optimized cost-effective maintenance program in developing countries where budget limitation is a big concern.

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Acknowledgements

The work presented in this paper was supported by State Council for Science, Technology & Environment (SCSTE), through financial support to carry out this research. The author would like to thank pavement maintenance planners of PMGSY and Himachal Pradesh Public Works Department (HPPWD) road maintenance engineers for their valuable expert advice and guidance.

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Authors and Affiliations

  1. Civil Engineering Department, Chandigarh University, Chandigarh, Punjab, 140413, India

    Akhilesh Nautiyal

  2. Civil Engineering Department, NIT Hamirpur, Hamirpur, 177005, India

    Sunil Sharma

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Correspondence to Akhilesh Nautiyal.

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Nautiyal, A., Sharma, S. Cost-Optimized Approach for Pavement Maintenance Planning of Low Volume Rural Roads: A Case Study in Himalayan Region. Int. J. Pavement Res. Technol. 17, 335–352 (2024). https://doi.org/10.1007/s42947-022-00239-x

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