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Record link: 
http://hdl.handle.net/20.500.12708/57476
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Title: 
Modeling and Solving an Automotive Paint Shop Scheduling Problem
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Citation: 
Winter, F., Musliu, N., Demirovic, E., & Mrkvicka, C. (2018). Modeling and Solving an Automotive Paint Shop Scheduling Problem. In 12th International Conference on the Practice and Theory of Automated Timetabling (pp. 477–480). http://hdl.handle.net/20.500.12708/57476
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
Authors: 
Winter, Felix 
Musliu, Nysret 
Demirovic, Emir 
Mrkvicka, Christoph 
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Organisational Unit: 
E192-02 - Forschungsbereich Databases and Artificial Intelligence 
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Published in: 
12th International Conference on the Practice and Theory of Automated Timetabling 
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Date (published): 
2018
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Event name: 
12th International Conference on the Practice and Theory of Automated Timetabling 
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Event date: 
28-Aug-2018 - 31-Aug-2018
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Event place: 
Wien, Austria
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Number of Pages: 
4
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Peer reviewed: 
Yes
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Keywords: 
Modeling; Automotive; Scheduling; Solving; Paint Shop
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Abstract: 
In this work, we introduce a novel scheduling problem that appears in the paint shops of the automotive supply industry. Although related problems like the car sequencing problem have been studied in the past (e.g. in [3], [4]), this problem includes unique features regarding the multi-objective minimization of sequence dependent changeover times, that to the best of our knowledge have not been described before. Furthermore, we create a collection of benchmark instances and propose a heuristic approach to solve the problem.
de
 
In this work, we introduce a novel scheduling problem that appears in the paint shops of the automotive supply industry. Although related problems like the car sequencing problem have been studied in the past (e.g. in [3], [4]), this problem includes unique features regarding the multi-objective minimization of sequence dependent changeover times, that to the best of our knowledge have not been described before. Furthermore, we create a collection of benchmark instances and propose a heuristic approach to solve the problem.
en
Project title: 
CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling (CDG Christian Doppler Forschungsgesellschaft) 
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Research Areas: 
Logic and Computation: 100%
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Science Branch: 
Informatik
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Appears in Collections:
Conference Paper

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