Abstract. In virtual cellular manufacturing, the processing lines are more complex, products are multi-varieties and small quantities, jobs spend 90% of the time waiting for the machine to be processed is common. In order to reduce the waiting time, this paper study the inter cell scheduling based on queuing network. The virtual cellular manufacturing system is seen as a queuing network, and the input parameters of each node within the network are calculated by the external arrival rate. Under the strategy of batch service. Scheduling target is minimize the total processing time, maximize the minimum of equipment load. Batch service queuing network model is established. The model is solved by the immune optimization algorithm, which achieves the shortest processing time, and avoids the parts waiting. Finally, taking the actual production process of ship enterprises as an example, it is proved that the batch service queuing network method is feasible and efficient.
Abstract. Aiming at the dynamic scheduling problem of virtual cellular generated by the random arrival of new tasks, combined with the rolling window technology, the decision-making judgment based on the order completion trigger and the machine idle state trigger is put forward. At the same time, the dynamic random scheduling period is divided into continuous interval of static scheduling. And a non-linear multi-objective 0-1 integer programming model is proposed, which is based on the maximum completion time, the weighted total delay and the initial scheduling degree of deviation as the targets. The multi-objective genetic algorithm is used to solve the model. Finally, taking the shipbuilding as an example, the feasibility and effectiveness of the rescheduling model are verified.
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