Musliu, N. (2024). AI Techniques for Timetabling and Scheduling Problems. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 5–5).
E192-02 - Forschungsbereich Databases and Artificial Intelligence E056-03 - Fachbereich BIOINTERFACE - Frontier Research in Nanotechnology and the Life Sciences
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Published in:
Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024
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ISBN:
978-0-9929984-6-2
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Date (published):
Aug-2024
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Event name:
14th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2024)
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Event date:
27-Aug-2024 - 30-Aug-2024
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Event place:
Copenhagen, Denmark
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Number of Pages:
1
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Peer reviewed:
Yes
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Keywords:
AI Techniques; Timetabling; Scheduling
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Abstract:
In this talk, we will first provide an overview of various AI-based methods proposed by our lab for solving problems in application domains such as employee timetabling and project scheduling. The topics covered will include solver-independent modelling, constraint programming, and hybrid techniques. In the second part of the talk, we will discuss methods that utilize machine learning techniques f...
In this talk, we will first provide an overview of various AI-based methods proposed by our lab for solving problems in application domains such as employee timetabling and project scheduling. The topics covered will include solver-independent modelling, constraint programming, and hybrid techniques. In the second part of the talk, we will discuss methods that utilize machine learning techniques for automatic algorithm selection and heuristic algorithm design. We will also briefly present innovative decision support systems that incorporate our solution methods and an approach for preference explanation to guide decision-makers toward solutions that align with their expectations. The talk will conclude with a discussion of future challenges in the domain of scheduling and timetabling.
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Project title:
CD Labor für Künstliche Intelligenz und Optimierung in Planung und Scheduling: keine Angabe (Christian Doppler Forschungsgesells)
