The Doctor Rostering Problem - Asser Fahrenholz

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Chapter 1 Introduction During the last five decades, growing interest in optimisation and efficiency has put focus on developing, not just valid schedules, but good schedules. Even though computerisa- tion and mathematics has come to the aid of a lot of workplaces, many still use manual scheduling to satisfy both production needs as well as employee happiness. Without the aid of decision support tools, the creation of a good solution for any non-trivial problem, takes overview, coordination and most importantly, time. In health care institutions, ward managers usually spends upwards 10 to 20 hours each quarter, or even monthly, to plan a good schedule, and even then, some needs are not met. Finally, measuring the quality of the schedule is troublesome, due to the constraints and the number of decisions that needs to be made. The medical practice in St. Heddinge houses six doctors, taking care of patients in the immediate vicinity, unless the patient needs hospitalisation. At least one of these six doctors must be available for treating acute patients during working hours. The Doctor Rostering Problem (DRP) is the problem of assigning one or more doctors to noon and afternoon shifts, in such a way that certain shift- and employee-requirements are met. In this thesis, I take a practical approach to solving the problem. 1.1 Purpose The purpose of this thesis is to: 1. Develop an objective function or cost function measuring the value of solutions for the DRP. 2. Provide a solution, within a relatively short amount of time, to the DRP. 1
Chapter 1. Introduction and problem context 2 3. Provide a software implementation that will allow the end user to find solutions. 1.2 Structure An introduction to the Doctor Rostering Problem (DRP) and a literary review is found in chapter 2. Chapter 3 contains a mathematical model for the hard and soft constraints. Through chapter 4, the problem complexity is analysed and the discussion of a construction heuristics, the GRASP framework and the Simulated Annealing algorithm for solving the problem is included along with the implementation of these methods. In chapter 5 a relaxed DRP problem is solved in GAMS and the solution is compared to solutions found by the heuristics. Chapter 6 describes the implementation of the DRP Program that will allow the medical practice to create their own schedules. In chapter 7 the performance of the heuristics is tested on a range of problems and the results are discussed. Through chapter 8, a discussion of future considerations and extensions to the solutions is found. Finally, in chapter 9 I summarise the conclusions from each individual chapter in this thesis.
Page 1 and 2: TECHNICAL UNIVERSITY OF DENMARK The
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Page 5 and 6: Acknowledgements Foremost, I would
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Appendix C. Tests 88 C.1.1 Instance
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Bibliography 118 [10] Michael R. Ga
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