Dynamic rescheduling with stability

Previously, most studies of job shop rescheduling problems only include efficiency in the objective function; consequently, the new schedule may be completely different from the previous schedule in order to obtain the optimal efficiency. Moreover, in the real manufacturing environment, costs not only arise when changes are made to the jobs in the original schedule but they are greater as changes are made closer to the current period. In this research, a multi-objective function that simultaneously addresses efficiency and stability is developed. A periodic rescheduling strategy is employed to determine when to construct a new schedule. A genetic local search algorithm is used to obtain a good schedule for the job shop problem in a dynamic environment. The results demonstrate that adding stability in the objective function can increase the stability of the schedule with slight effect on the efficiency.