Témata semestrálních projektů

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Název tématu Vedoucí Typ Kapacita Katedra vedoucího
Data-driven driven approach for scheduling Ing. Michal Bouška BM 0/1 13135

Popis
Deep learning is a rapidly growing discipline in the last ten years for many scientific disciplines. However, the way to utilize the neural network for scheduling is unclear and rarely studied in the literature[2]. Nevertheless, data-driven approaches have clear advantages for solving combinatorial problems, as has been shown in [1]. The target of the project is to propose an effective data-driven algorithm for the selected scheduling problem.
[1] Bouska, Novák, Šůcha, Módos, Hanzálek. "Data-driven Algorithm for Scheduling with Total Tardiness" ICORES. 2020.
[2] Vinyals, Oriol, Meire Fortunato, and Navdeep Jaitly. "Pointer networks." Advances in neural information processing systems. 2015.

Studijní program
KyR LK EECS EEK EEM EK EI SIT OI KME OES BII IB BIO

Za obsah odpovídá: doc. Ing. Ivan Jelínek, CSc.