Journal of Computational Physics
A Hyperheuristic Approach to Scheduling a Sales Summit
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
A Tabu-Search Hyperheuristic for Timetabling and Rostering
Journal of Heuristics
The State of the Art of Nurse Rostering
Journal of Scheduling
A comprehensive analysis of hyper-heuristics
Intelligent Data Analysis
Agent-based patient admission scheduling in hospitals
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track
Adaptive resource allocation for efficient patient scheduling
Artificial Intelligence in Medicine
A hybrid tabu search algorithm for automatically assigning patients to beds
Artificial Intelligence in Medicine
An experimental study on hyper-heuristics and exam timetabling
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
A shift sequence based approach for nurse scheduling and a new benchmark dataset
Journal of Heuristics
A categorisation of nurse rostering problems
Journal of Scheduling
Continual planning and scheduling for managing patient tests in hospital laboratories
Artificial Intelligence in Medicine
The effect of the set of low-level heuristics on the performance of selection hyper-heuristics
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Modeling and solving the dynamic patient admission scheduling problem under uncertainty
Artificial Intelligence in Medicine
A new hyper-heuristic as a general problem solver: an implementation in HyFlex
Journal of Scheduling
Hi-index | 0.00 |
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 hyper-heuristic approach, which is suitable for addressing two rather different timetabling problems in health care. It is applicable without much effort, provided a set of low-level heuristics is available for each problem. We consider the instances of both health 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.