An iterative exact algorithm solves a mixed-integer line planning model faster than CPLEX by dynamically expanding paths and frequencies, and accounting for lost demand improves overall resource efficiency.
Transit network design and scheduling: A global review
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Develops an AI-driven MINLP model that uses passenger demand forecasts to dynamically adjust pod dispatch schedules and train lengths for an adaptive air transit network.
citing papers explorer
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An Exact Algorithm for Public Transport Line Planning Considering Passenger and Operational Costs and Lost Demand
An iterative exact algorithm solves a mixed-integer line planning model faster than CPLEX by dynamically expanding paths and frequencies, and accounting for lost demand improves overall resource efficiency.
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AI-Driven Adaptive Air Transit Network with Modular Aerial Pods
Develops an AI-driven MINLP model that uses passenger demand forecasts to dynamically adjust pod dispatch schedules and train lengths for an adaptive air transit network.