Amirkabir University of Technology Amirkabir Journal of Civil Engineering 2588-297X 53 7 2021 09 23 Introducing a New Method for the Pavements’ Maintenance and Rehabilitation Planning Introducing a New Method for the Pavements’ Maintenance and Rehabilitation Planning 2801 2820 3853 10.22060/ceej.2020.17506.6585 FA Hamid Behbahani Professor, Iran University of Science and Technology Navid Nadimi Shahid Bahonar University of Kerman Mostafa Khaleghi M.Sc. Iran University of Science and Technology Journal Article 2019 12 10 Roads are considered as one of the most extensive civil infrastructures and national capitals of each country. Pavement maintenance and rehabilitation (M&R) management is one of the most important problems, which can help to reduce further costs. Two issues are important in the field of road maintenance and rehabilitation management; the first type of M&R option and then time its application. In this paper, it was attempted to combine prioritization, artificial intelligence, and optimization methods to select the optimal option for the maintenance and rehabilitation of pavement sections at any time interval. For this purpose, the analytical hierarchy process was used to prioritize the branches in the pavement network. In the next step, using a linear programming model, the probability of selecting maintenance and rehabilitation options for pavement sections was maximized considering several specific constraints. A fuzzy inference system was used to determine the probability of selecting each maintenance and rehabilitation option in pavement sections. A case study in Mahan (Kerman) was used to run the proposed model. Based on the results, it can be concluded that the proposed algorithm can consider different parameters and indices for pavement branches and sections. In addition, it offers different scenarios for the selection of M&R options in a year. The model helps to compare various scenarios based on different budgets for each year. In all, the proposed algorithm facilitates the process of selecting M&R options in the different sections of a road network and provides a scientific approach to manage maintenance roads. Roads are considered as one of the most extensive civil infrastructures and national capitals of each country. Pavement maintenance and rehabilitation (M&R) management is one of the most important problems, which can help to reduce further costs. Two issues are important in the field of road maintenance and rehabilitation management; the first type of M&R option and then time its application. In this paper, it was attempted to combine prioritization, artificial intelligence, and optimization methods to select the optimal option for the maintenance and rehabilitation of pavement sections at any time interval. For this purpose, the analytical hierarchy process was used to prioritize the branches in the pavement network. In the next step, using a linear programming model, the probability of selecting maintenance and rehabilitation options for pavement sections was maximized considering several specific constraints. A fuzzy inference system was used to determine the probability of selecting each maintenance and rehabilitation option in pavement sections. A case study in Mahan (Kerman) was used to run the proposed model. Based on the results, it can be concluded that the proposed algorithm can consider different parameters and indices for pavement branches and sections. In addition, it offers different scenarios for the selection of M&R options in a year. The model helps to compare various scenarios based on different budgets for each year. In all, the proposed algorithm facilitates the process of selecting M&R options in the different sections of a road network and provides a scientific approach to manage maintenance roads. https://ceej.aut.ac.ir/article_3853_b9f35816f460ab999cbc168c4da26ff3.pdf