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Sequencing and scheduling a form of making decision, which plays an important role in manufacturing business. In the present compete circumstance, in order to survive from the market, effective sequencing and scheduling has become increasingly important. During last5decade, the research on job shop scheduling problem has achieved many marvelous progresses, however, classic job shop scheduling is too idealized to direct production. Some deviations may come across in the actual production. Therefore, it is necessary to expand the classic problem to correspond with the real workshop. As an important production resource, whether machine is available or not relate to the performance of scheduling strategy and the cost of production. How to accurately avoid the unavailable time intervals of machines, ensure all jobs could process in a reasonable sequence, and meet the demand of every order, the significance of this problem is both in theory and practice.Firstly, according to the attribute of these unavailable time intervals, this paper divides the intervals into two kinds, deterministic and stochastic. Secondly, as for the job shop scheduling problem with deterministic time intervals, a new suitable model is built on base of classic job shop scheduling problem. Then a kind of Tabu search algorithm in ILOG circumstance is proposed. Meanwhile, dynamic rescheduling is used to solve the stochastic problem. A new drive method called self-adaption drive is proposed, and in order to consider both efficiency and stability, partial rescheduling and right-shift rescheduling are both used in this paper. Last but not least, some real data from Xi’an XXX Company has proved my models and strategies, in this paper, are accurate and effective.
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