Large-scale application of MILATRAS: case study of the Toronto transit network
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DOI: 10.1007/s11116-011-9358-5
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Cited by:
- Paulsen, Mads & Rasmussen, Thomas Kjær & Nielsen, Otto Anker, 2021. "Impacts of real-time information levels in public transport: A large-scale case study using an adaptive passenger path choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 155-182.
- Mohamed Wahba & Amer Shalaby, 2014. "Learning-based framework for transit assignment modeling under information provision," Transportation, Springer, vol. 41(2), pages 397-417, March.
- S. Mahmassani, Hani & F. Hyland, Michael, 2016. "Gap-based transit assignment algorithm with vehicle capacity constraints: Simulation-based implementation and large-scale applicationAuthor-Name: Verbas, Ömer," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 1-16.
- Kamel, Islam & Shalaby, Amer & Abdulhai, Baher, 2020. "A modelling platform for optimizing time-dependent transit fares in large-scale multimodal networks," Transport Policy, Elsevier, vol. 92(C), pages 38-54.
- Siva Srikukenthiran & Amer Shalaby, 2017. "Enabling large-scale transit microsimulation for disruption response support using the Nexus platform," Public Transport, Springer, vol. 9(1), pages 411-435, July.
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Keywords
Public transportation; Transportation models; Travel demand; Experiential learning; Genetic algorithm;All these keywords.
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