MILP-based campaign scheduling in a specialty chemicals plant: a case study

Marcus Brandenburg () and Franz-Josef Tölle ()
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Marcus Brandenburg: Beiersdorf AG
Franz-Josef Tölle: Bayer Business Services GmbH

A chapter in Supply Chain Planning, 2009, pp 315-340 from Springer

Abstract: Abstract Supply chain management in chemical process industry focuses on production planning and scheduling to reduce production cost and inventories and simultaneously increase the utilization of production capacities and the service level. These objectives and the specific characteristics of chemical production processes result in complex planning problems. To handle this complexity, advanced planning systems (APS) are implemented and often enhanced by tailor-made optimization algorithms. In this article, we focus on a real-world problem of production planning arising from a specialty chemicals plant. Formulations for finished products comprise several production and refinement processes which result in all types of material flows. Most processes cannot be operated on only one multi-purpose facility, but on a choice of different facilities. Due to sequence dependencies, several batches of identical processes are grouped together to form production campaigns. We describe a method for multicriteria optimization of short- and mid-term production campaign scheduling which is based on a time-continuous MILP formulation. In a preparatory step, deterministic algorithms calculate the structures of the formulations and solve the bills of material for each primary demand. The facility selection for each production campaign is done in a first MILP step. Optimized campaign scheduling is performed in a second step, which again is based on MILP. We show how this method can be successfully adapted to compute optimized schedules even for problem instances of real-world size, and we furthermore outline implementation issues including integration with an APS.

Keywords: Supply chain management; Campaign planning and scheduling; Chemical process industry; MILP; Advanced planning systems (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-93775-3_12

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DOI: 10.1007/978-3-540-93775-3_12

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