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.
Transportation Research Part C: Emerging Technologies137, 103573 (Apr 2022).https://doi
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Delineates P vs NP-hard boundaries for LiDARP and MinTurn by instance parameters and supplies parameterized algorithms.
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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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The Complexity of Counting Turns in the Line-Based Dial-a-Ride Problem
Delineates P vs NP-hard boundaries for LiDARP and MinTurn by instance parameters and supplies parameterized algorithms.