Models and Algorithms for Integration of Vehicle and Crew Scheduling
Journal of Scheduling
Simultaneous disruption recovery of a train timetable and crew roster in real time
Computers and Operations Research
Dynamic Aggregation of Set-Partitioning Constraints in Column Generation
Operations Research
A Robust Solution Approach to the Dynamic Vehicle Scheduling Problem
Transportation Science
Simultaneous vehicle and driver scheduling: A case study in a limousine rental company
Computers and Industrial Engineering
Set partitioning/covering-based approaches for the integrated vehicle and crew scheduling problem
Computers and Operations Research
Bi-dynamic constraint aggregation and subproblem reduction
Computers and Operations Research
Simultaneous Vehicle and Crew Scheduling for Extra Urban Transports
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
On the choice of explicit stabilizing terms in column generation
Discrete Applied Mathematics
A new version of the Improved Primal Simplex for degenerate linear programs
Computers and Operations Research
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Truck Driver Scheduling in the European Union
Transportation Science
The modeling power of the periodic event scheduling problem: railway timetables-and beyond
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
Assigning multiple activities to work shifts
Journal of Scheduling
A heuristic to solve the synchronized log-truck scheduling problem
Computers and Operations Research
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This paper presents an exact approach for solving the simultaneous vehicle and crew scheduling problem in urban mass transit systems. We consider the single depot case with a homogeneous fleet of vehicles. This approach relies on a set partitioning formulation for the driver scheduling problem that incorporates side constraints for the bus itineraries. The proposed solution approach consists of a column generation process (only for the crew schedules) integrated into a branch-and-bound scheme. The side constraints on buses guarantee that an optimal vehicle assignment can be derived afterwards in polynomial time. A computational study shows that this approach out-performs the previous methods found in the literature for a set of randomly generated instances. A heuristic version of the solution approach is also proposed and tested on larger instances.