The personnel scheduling is a well-known NP-hard combinatorial problem. Due to the complexity of this problem and the size of the real-world instances finding of the optimal or a near optimal solution is not a trivial task. The aim of this topic is to outperform the state-of-the-art exact and heuristic algorithms on the new benchmark instances available at http://www.cs.nott.ac.uk/~psztc/NRP/#new_instances. The topic addresses the development of highly parallel algorithms and use of deep neural networks.
Bäumelt, Z. - Dvořák, J. - Šůcha, P. - Hanzálek, Z. A Novel Approach for the Nurse Rerostering Problem based on a Parallel Algorithm In: European Journal of Operational Research. 2016, vol. 251, no. 2, p. 624-639.
Václavík R. - Šůcha, P. - Hanzálek, Z. Roster evaluation based on classifiers for the nurse rostering problem In: Journal of Heuristics . 2016, vol. 22, no. 5, pp. 667-697.
Bäumelt, Z. - Šůcha, P. - Hanzálek, Z. A Multistage Approach for an Employee Timetabling Problem with a High Diversity of Shifts as a Solution for a Strongly Varying Workforce Demand In: Computers & Operations Research. 2014, vol. 49, p. 117–129.