An evaluation of certain heuristic optimization algorithms in scheduling medical doctors and medical students

Authors:
Christine A. White;Emilina Nano;Diem-Hang Nguyen-Ngoc;George M. White
Affiliations:
Department of Medicine, Division of Nephrology, Queen's University, Kingston, Canada;School of Information Technology and Engineering, University of Ottawa, ON, Canada;School of Information Technology and Engineering, University of Ottawa, ON, Canada;School of Information Technology and Engineering, University of Ottawa, ON, Canada
Venue:
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Year:
2006

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Abstract

Four heuristic algorithms based on or inspired by the well-known Tabu Search method have been used to cast heuristically optimized schedules for a clinical training unit of a hospital. It has been found experimentally that the algorithm of choice for this problem depends on the exact goal being sought where the execution time is one of the components of the goal. If only one run is allowed, then classical Tabu Search with a tenure of 5 gave the schedule with the lowest average (and fixed) penalty. If time is not of concern and many runs are allowed then the Great Deluge algorithm may generate the schedule with the lowest penalty.