In this paper, a disruption recovery model is developed for an imperfect single-stage production–inventory
system. For it, the system may unexpectedly face either a single disruption or a mix of multiple
dependent and/or independent disruptions. The system is usually run according to a user defined production–
inventory policy. We have formulated a mathematical model for rescheduling the production plan,
after the occurrence of a single disruption, which maximizes the total profit during the recovery time
window. The model thereby generates a revised plan after the occurrence of the disruption. The mathematical
model, developed for a single disruption, is solved by using both a pattern search and a genetic
algorithm, and the results are compared using a good number of randomly generated disruption test
problems. We also consider multiple disruptions, that occur one after another as a series, for which a
new occurrence may or may not affect the revised plan of earlier occurrences. We have developed a
new dynamic solution approach that is capable of dealing with multiple disruptions on a real-time basis.
Some numerical examples and a set of sensitivity analysis are presented to explain the usefulness and
benefits of the developed model. The proposed quantitative approach helps decision makers to make
prompt and accurate decisions for managing disruption.