Abstract:
Disclosed is method and system for continuously re-generating reactive on-line train schedules for trains running in a large railway network. Railway network partitioned based on user configuration, into first type comprising trunk line and feeder line sub-networks, and second type comprising supervisory dispatch control territories. Sense and respond cycle is continuously executed on multi-processor computing environment, senses dynamic data from field about train movements, and other changes from users. For each first type sub-network, degree of deviation is computed from incumbent plans and congestion in sub-networks. Using degree of deviation and congestion, trains are rerouted and suitable scheduling methods are chosen for each sub-network and executed in parallel and first level train schedules are sent to second level train schedulers working on second type sub-networks which in parallel identify and resolve conflicts among first level train schedules. Second level train schedules are collated to generate reactive on-line network train schedule.