Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Cyclic schedules for r irregularly occurring events
Journal of Computational and Applied Mathematics
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Computers and Operations Research
Modern heuristic techniques for combinatorial problems
A fast heuristic for the train scheduling problem
Computers and Operations Research
Handbook of Evolutionary Computation
Handbook of Evolutionary Computation
Solution of Real-World Train Timetabling Problems
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 3 - Volume 3
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An adaptive scheduling system with genetic algorithms for arranging employee training programs
Expert Systems with Applications: An International Journal
Neuro-dynamic programming with recurrent critic for automatic train regulation of metro line
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Modelling disruptions and resolving conflicts optimally in a railway schedule
Computers and Industrial Engineering
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A new train operation model proposed here not only considers the flexibility of train regulation, or train rescheduling problem, but also the objectives of timetabling process. A genetic algorithm is applied to solve this problem efficiently. Thus no matter the problem is planning the timetable of trains, the unusual passenger flow occurrence or the incident caused delay, our model will make the train regulation as the same as the timetable construction. This will simplify the work of administration. Our model also shows that once the delay occurred, the waiting time of the passengers will be the cost to delay every train. If the delay is not large enough, the system can have some rooms for removing the influence of the delay through our model.