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The job scheduling problem (JSP) is considered as one of the complex combinatorial optimization problems. In this paper, we have developed a hybrid Genetic Algorithm (HGA), which improves the performance of GAs when solving JSPs. We have also modified the developed algorithm to study JSPs under the machine unavailability condition. We have considered two types of machine unavailability. Firstly, where the unavailability information is available in advance (predictive) and, secondly, where the information is known after a real breakdown (reactive). We have shown that the revised schedule is mostly able to recover if the disruptions occur during the early stages of a schedule.