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cs.LG2025
Applications of deep reinforcement learning to urban transit network design
Andrew Holliday
This thesis concerns the use of reinforcement learning to train neural networks to aid in the design of public transit networks. The Transit Network Design Problem (TNDP) is an opt…
cs.LG2024★ 2 cited
Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learning
Andrew Holliday, Ahmed El-Geneidy, Gregory Dudek
Planning a network of public transit routes is a challenging optimization problem. Metaheuristic algorithms search through the space of possible transit networks by applying heuris…