Optimization of a planning algorithm in the brewery industry
Bottling planning in the brewery industry has a great impact on costs. The goal of this Thesis is to optimize an existing bottling planning algorithm so that machine capacities are optimally used by minimizing overall setup times and optimizing lot sizes.
Antje Obatolu, 2018
Bachelor Thesis, Imecon AG
Betreuende Dozierende: Thomas Hanne
Keywords: Bottling planning, algorithm, optimization, brewery industry, operations research, Tabu Search
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Over the past few years, breweries have been facing a trend towards larger assortments in terms of different bottle shapes or colors as well as different labels or packing units.
With more products to be bottled in the same time horizon, changeovers from one product to another are also increasing.
Longer overall setup times reduce the availability of the bottling machines which has a direct impact on costs.
The specific planning problem is analyzed and compared to other common planning problems in Operations Research literature.
Different categories of algorithms are explored and an algorithm suitable for this planning problem is recommended.
A concept tailored to the specific needs is developed and presented.
Additionally, the recommended Tabu Search algorithm is implemented in a proof-of-concept using Java as programming language.
Studiengang: Business Information Technology (Bachelor)
Fachbereich der Arbeit: Logistik & Beschaffung