To close the gap between scheduling theory and practice from unrealistic assumptions
a method for integrating job-shop scheduling(JSP)and preventive maintenance(PM)is proposed. The original scheduling plan is generated by genetic algorithm
where the setup time is taken into account. Then the preventive maintenance plan for each machine according to the assigned tasks of the machine and its failure probability distribution is adaptively determined. The original schedule meanwhile should be slightly modified by right-shifting strategy according to inserted time intervals for PM activities
thus the optimal integrated plan of JSP and PM is obtained. A classical benchmark instance is extended and used to verify the effectiveness of the proposed method. The comparative results show that the explicit consideration of the setup time improves the scheduling performances and makes the PM plan generated according to the machining time and failure probability distribution much more reasonable.
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references
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