Using aggregate estimation models for order acceptance in a decentralized production control structure for batch chemical manufacturing

W.H.M. Raaymakers, J.W.M. Bertrand, J.C. Fransoo

Research output: Contribution to journalArticleAcademicpeer-review

19 Citations (Scopus)
123 Downloads (Pure)

Abstract

Aggregate models of detailed scheduling problems are needed to support aggregate decision making such as customer order acceptance. In this paper, we explore the performance of various aggregate models in a decentralized control setting in batch chemical manufacturing (no-wait job shops). Using simulation experiments based on data extracted from an industry application, we conclude that a linear regression based model outperforms a workload based model with regard to capacity utilization and the need for replanning at the decentralized level, specifically in situations with increased capacity utilization and/or a high variety in the job mix.
Original languageEnglish
Pages (from-to)989-998
JournalIIE Transactions
Volume32
Issue number10
DOIs
Publication statusPublished - 2000

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