Computers and Operations Research
A survey on benders decomposition applied to fixed-charge network design problems
Computers and Operations Research
Efficient Circulation of Railway Rolling Stock
Transportation Science
Circulation of railway rolling stock: a branch-and-price approach
Computers and Operations Research
Benders decomposition for the uncapacitated multiple allocation hub location problem
Computers and Operations Research
Benders Decomposition for Hub Location Problems with Economies of Scale
Transportation Science
Multiple allocation hub-and-spoke network design under hub congestion
Computers and Operations Research
A hybrid algorithm for capacitated plant location problem
Expert Systems with Applications: An International Journal
Robust rolling stock in rapid transit networks
Computers and Operations Research
A search-based approach to the railway rolling stock allocation problem
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part II
Estimates on rolling stock and crew in DSB S-tog based on timetables
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
Rotation planning of locomotive and carriage groups with shared capacities
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
Benders Decomposition for Large-Scale Uncapacitated Hub Location
Operations Research
Practical enhancements to the Magnanti-Wong method
Operations Research Letters
Exact Solution of Large-Scale Hub Location Problems with Multiple Capacity Levels
Transportation Science
A Lagrangian heuristic for a train-unit assignment problem
Discrete Applied Mathematics
Hi-index | 0.00 |
One of the many problems faced by rail transportation companies is to optimize the utilization of the available stock of locomotives and cars. In this paper, we describe a decomposition method for the simultaneous assignment of locomotives and cars in the context of passenger transportation. Given a list of train legs and a fleet composed of several types of equipment, the problem is to determine a set of minimum cost equipment cycles such that every leg is covered using appropriate equipment. Linking constraints, which appear when both locomotives and cars are treated simultaneously, lead to a large integer programming formulation. We propose an exact algorithm, based on the Benders decomposition approach, that exploits the separability of the problem. Computational experiments carried on a number of real-life instances indicate that the method finds optimal solutions within short computing times. It also outperforms other approaches based on Lagrangian relaxation or Dantzig--Wolfe decomposition, as well as a simplex-based branch-and-bound method.