Vass, J., Musliu, N., & Winter, F. (2022). Solving the Production Leveling Problem with Order-Splitting and Resource Constraints. In Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling (pp. 261–284). http://hdl.handle.net/20.500.12708/142211
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Published in:
Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling
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ISBN:
978-0-9929984-3-1
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Volume:
I
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Date (published):
2022
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Event name:
PATAT 2022 - 13th International Conference on the Practice and Theory of Automated Timetabling
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Event date:
30-Aug-2022 - 2-Sep-2022
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Event place:
Leuven, Belgium
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Number of Pages:
24
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Peer reviewed:
Yes
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Keywords:
Production Leveling; Simulated Annealing; MIP
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Abstract:
We investigate an extended problem formulation of the Production Leveling Problem (PLP), which was recently introduced in the literature. For the PLP problem the task is to assign orders to production periods such that the load is balanced, capacity limits are not exceeded and the order’s priorities are considered. The extended problem (PLP-OSRC) introduced in this paper additionally includes order-splitting, resource constraints and due dates. We provide a mixed integer programming formulation for the PLP-OSRC based on the existing model for the PLP and evaluate it with a state-of-the-art MIP solver. To solve practically sized instances we apply a local search approach based on simulated annealing and propose two innovative neighborhood moves. We compare our approaches on two sets of randomly generated instances and show that the simulated annealing approach provides competitive results to MIP for the smaller instances. Moreover, it provides good solutions for very large instances that could not be solved by our MIP model in a reasonable amount of time.
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Project title:
CD Labor für Künstliche Intelligenz und Optimierung in Planung und Scheduling: keine Angabe (CDG Christian Doppler Forschungsgesellschaft)