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Dynamic rescheduling that simultaneously considers efficiency and stability
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DOI：10.1016/j.cie.2003.09.007.png)
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Abstract
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Dynamic job shop scheduling is a frequently occurring and highly relevant problem in practice. Previous research suggests that periodic rescheduling improves classical measures of efficiency; however, this strategy has the undesirable effect of compromising stability and this lack of stability can render even the most efficient rescheduling strategy useless on the shop floor. In this research, a rescheduling methodology is proposed that uses a multiobjective performance measures that contain both efficiency and stability measures. Schedules are generated at each rescheduling point using a genetic local search algorithm that allows efficiency and stability to be balanced in a way that is appropriate for each situation. The methodology is tested on a simulated job shop to determine the impact of the key parameters on the performance measures. (C) 2003 Elsevier Ltd. All rights reserved.
Keywords:
dynamic scheduling
genetic local search
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