The fixed job schedule problem with spread-time constraints
Operations Research
Vehicle scheduling in public transit and Lagrangean pricing
Management Science
A Column Generation Approach for Large-Scale Aircrew Rostering Problems
Operations Research
A Heuristic Method for the Set Covering Problem
Operations Research
Simultaneous Vehicle and Crew Scheduling in Urban Mass Transit Systems
Transportation Science
Models and Algorithms for Integration of Vehicle and Crew Scheduling
Journal of Scheduling
Multiple-Depot Integrated Vehicle and Crew Scheduling
Transportation Science
Set partitioning/covering-based approaches for the integrated vehicle and crew scheduling problem
Computers and Operations Research
A comparison of five heuristics for the multiple depot vehicle scheduling problem
Journal of Scheduling
Integrated Airline Fleeting and Crew-Pairing Decisions
Operations Research
On an exact method for the constrained shortest path problem
Computers and Operations Research
Management of Bus Driver Duties Using Data Mining
International Journal of Applied Metaheuristic Computing
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This paper discusses the integrated vehicle-and crew-scheduling problem in public transit with multiple depots. It is well known that the integration of both planning steps discloses additional flexibility that can lead to gains in efficiency, compared to sequential planning. We present a new modeling approach that is based on a time-space network representation of the underlying vehicle-scheduling problem. The integrated problem is solved with column generation in combination with Lagrangian relaxation. The column generation subproblem is modeled as a resource-constrained shortest-path problem based on a novel time-space network formulation. Feasible solutions are generated by a heuristic branch-and-price method that involves fixing service trips to depots. Numerical results show that our approach outperforms other methods from the literature for well-known test problems.