Research literature generally cover scheduling of transportation services . Disruptions happen while a schedule is en-route and there are very few mathematical models that address to reschedule the disrupted services at the moment and location where disruption has occured. The model reported in this note attempts to reschedule disrupted services with a goal to restore services as early as possible. Mathematically, this translates to minimizing the total delay incurred by all scheduled services in reaching their respective destinations. The model allows a host of hard/soft constraints to facilitate transportation services and parametric changes, if needed.