Multiple-order permutation flow shop scheduling under process interruptions

The permutation flow shop problem is a complex combinatorial optimization problem. Over the last few decades, a good number of algorithms have been proposed to solve static permutation flow shop problems. However, in practice, permutation flow shop problems are not static but rather are dynamic because the orders (where each order contains multiple jobs) arrive randomly for processing and the operation of any job may be interrupted due to resource problems. For any interruption, it is necessary to reschedule the existing jobs that are under process at different stages in the production system and also any orders that were previously accepted that are waiting for processing. In this paper, a memetic algorithm-based rescheduling approach has been proposed to deal with both single and multiple orders while considering random interruptions of resources. The experimental results have shown that the performance of the proposed approach is superior to traditional reactive approaches.