With urbanization and diversification of travelers' needs, railway schedules have become increasingly more complicated and congested, leading to longer restoration time when schedules are disrupted through disaster or accidents. It is also expected that such schedule restoration know-how will become increasingly difficult to pass-on in training. Using the latest operations research (OR) and knowledge engineering technologies, a scheduling system platform and related applications are being developed to effectively support tasks requiring human know-how and judgment, such as resource allocation, railway traffic-control simulations, depot shunting, and so on.
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