Scheduling batch processing in flexible flowshop with job dependent buffer requirements: Lagrangian relaxation approach

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Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 10755 LNCS pp. 119 - 131
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© Springer International Publishing AG, part of Springer Nature 2018. The paper presents a Lagrangian relaxation based algorithm for scheduling jobs in the two-stage flowshop where the first stage is comprised of several parallel identical machines and the second stage consists of a single machine processing jobs in the predefined batches. Motivated by applications where unloading and loading occur when the means of transportation are changed, the processing of the jobs, constituting a batch, can commence only if this batch has been allocated a portion of a limited buffer associated with the flowshop. This portion varies from batch to batch and is released only after the completion of the batch processing on the second stage machine. Each batch has a due date and the objective is to minimise the total weighted tardiness. The effectiveness of the proposed algorithm is demonstrated by computational experiments.
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