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  • This is an extended abstract about roster evaluation based on the classifiers for the nurse rostering problem which is a well-known combinatorial problem. Various heuristics dealing with this problem can be found in the literature. However, they have to evaluate many intermediate rosters which is very time consuming process. In our paper, we propose a faster roster evaluation using the pattern recognition to determine how much good or bad the rosters are. The experimental results show a significant algorithm runtime reduction in comparison with standard evaluation.
  • This is an extended abstract about roster evaluation based on the classifiers for the nurse rostering problem which is a well-known combinatorial problem. Various heuristics dealing with this problem can be found in the literature. However, they have to evaluate many intermediate rosters which is very time consuming process. In our paper, we propose a faster roster evaluation using the pattern recognition to determine how much good or bad the rosters are. The experimental results show a significant algorithm runtime reduction in comparison with standard evaluation. (en)
Title
  • Roster Evaluation Based on the Classifiers for the Nurse Rostering Problem
  • Roster Evaluation Based on the Classifiers for the Nurse Rostering Problem (en)
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  • Roster Evaluation Based on the Classifiers for the Nurse Rostering Problem
  • Roster Evaluation Based on the Classifiers for the Nurse Rostering Problem (en)
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  • RIV/68407700:21230/13:00208840!RIV14-MSM-21230___
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  • 103484
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  • RIV/68407700:21230/13:00208840
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  • nurse rostering problem; pattern learning; neural network; adaptive boosting (en)
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  • [59E90083BD7B]
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  • Hanzálek, Zdeněk
  • Šůcha, Přemysl
  • Václavík, Roman
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  • 21230
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