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Project description: Developing a hierarchical decision-making framework for planning network-scale maintenance activities on the network of bridges in the province of Quebec.

Funding: Quebec Transportation Ministry (MTQ)

Development Methods: Reinforcement Learning, Deep Q-Learning, Artificial Neural Network, Kalman Filter & Smoother, Gaussian Mixture Reduction

Development Tools: Python (Including: Pytorch, Ray, TensorBoard), MATLAB (Including: App Designer), Github.

Open-source Software: InfraPlanner

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Resources

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[2024]:

Quantifying the relative change in maintenance costs due to delayed maintenance actions on transportation infrastructure.
Z. Hamida, J-A. Goulet
Journal of Performance of Constructed Facilities
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[2023]:

Maintenance Planning for Bridges Using Hierarchical Reinforcement Learning.
Z. Hamida, J-A. Goulet
14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14, Dublin, Ireland.
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Hierarchical Reinforcement Learning for Transportation Infrastructure Maintenance Planning.
Z. Hamida, J-A. Goulet
Reliability Engineering and System Safety.
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