The Flow Must Go On

Algorithms for Scheduling in Biomanufacturing

Doctoral Thesis (2026)
Author(s)

K.C. van den Houten (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

M.M. de Weerdt – Promotor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

D.M.J. Tax – Copromotor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Algorithmics
DOI related publication
https://doi.org/10.4233/uuid:08d226bd-4005-45a8-92b2-adca5c14b39a Final published version
More Info
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Publication Year
2026
Language
English
Defense Date
03-06-2026
Awarding Institution
Delft University of Technology
Research Group
Algorithmics
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Abstract

Biomanufacturing involves the large-scale production of bio-based products, for example, food ingredients. In fermentation-based factories, living organisms are used to produce the active components of these bio-based products through fermentation in large bioreactors. Modern biomanufacturing plants are highly complex, with many tanks and interconnected pieces of equipment. They are typically designed to make multiple products (in parallel), each with its own recipe and production process. As a result, it is not possible to repeat the same weekly schedule—customer demand changes over time, and different customer orders require different products and thus production schedules.
A feasible schedule should consider several scheduling rules essential for biomanufacturing. For example, in the food industry, it is crucial that tanks are cleaned before, after, or between specific production operations. The production of a single product involves multiple unit operations, for example, starting from fermentation, followed by several filtration steps. Between the different stages, there are rules about how long an intermediate product can wait at a single tank; otherwise, a product risks expiring. Due to the biological nature of fermentation processes, process durations are uncertain and can vary from batch to batch. Due to this complexity, limited resource capacities, and various sources of uncertainty, it poses a significant challenge for factory managers and production planners to fulfill all customer orders on time.....

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