We present one general high-level hyper-heuristic approach for addressing two timetabling problems in the health care domain: the patient admission scheduling problem and the nurse rostering problem. The complex combinatorial problem of patient admission scheduling has only recently been introduced to the research community. In addition to the instance that was introduced on this occasion, we present a new set of benchmark instances. Nurse rostering, on the other hand, is a well studied operations research problem in health care. Over the last years, a number of problem definitions and their corresponding benchmark instances have been introduced. Recently, a new nurse rostering problem description and datasets were introduced during the first Nurse Rostering Competition. In the present paper, we focus on this nurse rostering problem description.The main contribution of the paper constitutes the introduction of a general hyperheuristic approach, which is suitable for addressing two rather different timetabling problems in health care. It is applicable without much effort, provided a set of lowlevel heuristics is available for each problem. We consider the instances of both health B. Bilgin · P. Demeester ( ) · M. Misir · W.B. Bilgin et al.care problems for testing the general applicability of the hyper-heuristic approach. Also, improvements to the previous best results for the patient admission scheduling problem are presented. Solutions to the new nurse rostering instances are presented and compared with results obtained by an integer linear programming approach.
We propose one general hyperheuristic approach for addressing two timetabling problems in the health care domain: the patient admission scheduling and the nurse rostering problem. The complex combinatorial problem of patient admission scheduling has only recently been introduced to the research community. In addition to the benchmark instance that was recently introduced, we present six new benchmark instances. A comparison between the hyperheuristic and previously developed approaches reveals a significant outperformance of the new solution method. Nurse rostering, on the other hand, is a well studied health care operation research problem. Until now, not many nurse rostering benchmark instances existed. Only very recently, several nurse rostering data sets were introduced during the First Nurse Rostering Competition. We show that one hyperheuristic can tackle both health care timetabling problems with good results.
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