A new lot sizing and scheduling heuristic for multi-site biopharmaceutical production

Folarin B. Oyebolu (), Jeroen Lidth de Jeude (), Cyrus Siganporia (), Suzanne S. Farid (), Richard Allmendinger () and Juergen Branke ()
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Folarin B. Oyebolu: University of Warwick
Jeroen Lidth de Jeude: University of Warwick
Cyrus Siganporia: University College London
Suzanne S. Farid: University College London
Richard Allmendinger: University of Manchester
Juergen Branke: University of Warwick

Journal of Heuristics, 2017, vol. 23, issue 4, No 3, 256 pages

Abstract: Abstract Biopharmaceutical manufacturing requires high investments and long-term production planning. For large biopharmaceutical companies, planning typically involves multiple products and several production facilities. Production is usually done in batches with a substantial set-up cost and time for switching between products. The goal is to satisfy demand while minimising manufacturing, set-up and inventory costs. The resulting production planning problem is thus a variant of the capacitated lot-sizing and scheduling problem, and a complex combinatorial optimisation problem. Inspired by genetic algorithm approaches to job shop scheduling, this paper proposes a tailored construction heuristic that schedules demands of multiple products sequentially across several facilities to build a multi-year production plan (solution). The sequence in which the construction heuristic schedules the different demands is optimised by a genetic algorithm. We demonstrate the effectiveness of the approach on a biopharmaceutical lot sizing problem and compare it with a mathematical programming model from the literature. We show that the genetic algorithm can outperform the mathematical programming model for certain scenarios because the discretisation of time in mathematical programming artificially restricts the solution space.

Keywords: Evolutionary algorithm; Heuristics; Scheduling; Biopharmaceutical manufacture; Capacity planning; Construction heuristic (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10732-017-9338-9

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