Disruption management for machine scheduling: The case of shortest processing time schedules

This paper addresses the problem of updating a machine schedule when either a random or an anticipated disruption occurs after a subset of the jobs has been processed. In such cases, continuing with the original schedule is likely to be suboptimal and may not even be feasible. The approach taken here differs from most rescheduling analysis in that the cost associated with the deviation between the original and the new schedule is included in the model. We concentrate on cases in which the shortest processing time (SPT) rule is optimal for the original problem. Both single and parallel two-machine environments are considered.