Abstract
We propose a new time-bucket MILP model for lot-sizing and scheduling problems arising in multistage production processes. The time-bucket model benefits from advantages of both continuous and discrete time representations while overcoming their shortcomings. In particular, we show how the time-bucket model allows to easily include a variety of typical, important real-world constraints, can be solved with moderate computer effort, and thus promotes MILP for large-scale, industrial problems. To illustrate that, we apply the time-bucket approach to the flow shop problem of a batch formulation and filling process from an industrial pesticide production. We reconcile the MILP solution with a validated discrete event simulation (DES) model of the process to obtain optimal and real-world feasible results. A comparison of the MILP-DES solution to a manually optimized solution for a one-month production data set shows that more than 17% of production capacity can be freed up and significant improvement in on-time delivery.
Original language | English |
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Title of host publication | 33rd European Symposium on Computer Aided Process Engineering |
Publisher | Elsevier |
Pages | 1853-1859 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 18 Jul 2023 |
Event | 33rd European Symposium on Computer Aided Process Engineering, ESCAPE 2023 - Athens, Greece Duration: 18 Jun 2023 → 21 Jun 2023 Conference number: 33 |
Publication series
Name | Computer Aided Chemical Engineering |
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Volume | 52 |
ISSN (Print) | 1570-7946 |
Conference
Conference | 33rd European Symposium on Computer Aided Process Engineering, ESCAPE 2023 |
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Abbreviated title | ESCAPE 2023 |
Country/Territory | Greece |
City | Athens |
Period | 18/06/23 → 21/06/23 |
Keywords
- Discrete event systems in manufacturing
- Mixed-integer linear programming
- Modeling of manufacturing operations
- Production planning and scheduling
- NLA