The Doctor Rostering Problem - Asser Fahrenholz

Recommendations

Info

Chapter 2 The Doctor Rostering Problem In this chapter, I present the background for the problem, the specific problem concepts and review literary sources that have served as inspiration to this project. 2.1 Background Every four months, one of the doctors at the medical practice in St. Heddinge 1 , schedules the treatment of the acute patients in the immediate vicinity. This treatment must be done by one or two of the six doctors, subject to higher workloads after weekends and holidays and before holidays (somehow, people can avoid getting ill during holidays). The scheduling is done with no computer aided support, takes approximately five to ten hours and is tedious due to required gathering of available hours from each individual member of the workforce. The information tells the planner which doctor is available when, during the next four months. The planner must then assign the doctors to shifts in such a way that certain shift-patterns are avoided and such that every member of the workforce receives equally many shifts. This approach to schedule planning, performed by an employee without decision support tools, is often called self-scheduling (Burke et al. [5]). The schedule planned by the doctor is chosen to be non-cyclical, or flexible (Silvestro and Silvestro [22]), due to the medical practice being a private one, where the members of the workforce prefer ad-hoc schedules. This problem is similar in nature to the Nurse Scheduling Problem (NSP) (or Staff Scheduling Problem). NSP is the problem of assigning a fleet of nurses to shifts of varying types, in a period of time. The assignments must respect both personal wishes 1 South-east of Køge, Denmark 3
Chapter 2. The Doctor Rostering Problem 4 along with holidays and union contract stipulations. This problem is the main source of inspiration for this project. Another problem that shows similar features is the Gotlieb Class-Teacher Problem (or Timetable Design Problem) of assigning teachers to classes, in such a way that every class has one teacher and no teacher has two classes at the same time. Very little material has been found on this, but an important contribution by this field, shall be noted in chapter 4. 2.1.1 The staff As opposed to a public health care institution, where the staff is subject to a range of stipulations and union contracts, the planner in this project has a much higher degree of control over the work flow of the institution. As the private institution is not subject to the same form of bureaucracy (due to the small size and being private), the constraints are not based upon public requirements, but rather personal requests and experiences. This is a direct consequence of the joint owners of the office controlling their own working hours and thereby controlling their pay. In typical NSP, the staff consist of a large number of nurses, divided into categories based on their qualification level and responsibilities. Several degrees of qualification can exist allowing a lower qualified member of the staff to be replaced by a higher qualified member. The staff can also be divided into full time or part time employees and some NSPs require higher qualified members to supervise the lower qualified members. In the context of this project, the staff that needs assigning are not divided into qualification groups. Due to decisions made in the practice, any interns/nurses in the practice will be assigned shifts manually. 2.1.2 Shift types This project deals with four shift types: night-, noon-, afternoon- and evening shifts. The night- and evening shifts are given through a public body and can not be changed, leaving the noon- and afternoon shifts to be assigned. One or two doctors must be assigned to these two shifts. A standard NSP contains the three shifts: night-, day- and evening shifts, and most often requires more than one nurse to be assigned to the shift.
Page 1 and 2: TECHNICAL UNIVERSITY OF DENMARK The
Page 3 and 4: TECHNICAL UNIVERSITY OF DENMARK Abs
Page 5 and 6: Acknowledgements Foremost, I would
Page 7 and 8: Contents vi 4.3.1 A construction he
Page 9 and 10: List of Figures 4.1 The transformat
Page 11 and 12: List of Algorithms 4.1 Adaptive gre
Page 13: Chapter 1. Introduction and problem
Page 17 and 18: Chapter 2. The Doctor Rostering Pro
Page 19 and 20: Chapter 3 A mathematical model for
Page 21 and 22: Chapter 3. The model and design 10
Page 27 and 28: Chapter 4. Solving the DRP 16 it in
Page 29 and 30: Chapter 4. Solving the DRP 18 4.3.1
Page 31 and 32: Chapter 4. Solving the DRP 20 Given
Page 33 and 34: Chapter 4. Solving the DRP 22 Since
Page 35 and 36: Chapter 4. Solving the DRP 24 1. Co
Page 37 and 38: Chapter 4. Solving the DRP 26 decre
Page 39 and 40: Chapter 4. Solving the DRP 28 This
Page 41 and 42: Chapter 4. Solving the DRP 30 Simul
Page 43 and 44: Chapter 5. Optimal solution 32 The
Page 45 and 46: Chapter 6 The DRP Program Through t
Page 47 and 48: Chapter 6. The DRP Program 36 Figur
Page 49 and 50: Chapter 6. The DRP Program 38 of th
Page 51 and 52: Chapter 6. The DRP Program 40 Figur
Page 53 and 54: Chapter 7 Metaheuristic tests This
Page 55 and 56: Chapter 7. Tests, results and discu
Page 65 and 66:
Chapter 8. Future considerations 54
Page 67 and 68:
Chapter 8. Future considerations 56
Page 69 and 70:
Chapter 9. Conclusion 58 The three
Page 71 and 72:
Appendix A. Implementation 60 27 //
Page 73 and 74:
2 Appendix A. Implementation 62 3 i
Page 75 and 76:
Appendix A. Implementation 64 A.3 G
Page 77 and 78:
Appendix A. Implementation 66 97 wh
Page 79 and 80:
Appendix A. Implementation 68 27 su
Page 81 and 82:
Appendix A. Implementation 70 119 P
Page 83 and 84:
Appendix A. Implementation 72 64 br
Page 85 and 86:
Appendix A. Implementation 74 28 Ch
Page 87 and 88:
Appendix B GAMS Model This chapter
Page 89 and 90:
Appendix B. GAMS Model 78 46 c(day
Page 91 and 92:
Appendix B. GAMS Model 80 109 B1( f
Page 93 and 94:
Appendix B. GAMS Model 82 **** REPO
Page 95 and 96:
Appendix B. GAMS Model 84 B.3 The s
Page 97 and 98:
Appendix B. GAMS Model 86 B.3.3 The
Page 99 and 100:
Appendix C. Tests 88 C.1.1 Instance
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Appendix C. Tests 94 JST PZH HP SDA
Page 107 and 108:
Appendix C. Tests 96 JST PZH HP SDA
Page 109 and 110:
Page 111 and 112:
Appendix C. Tests 100 Cons 12 Imps
Page 113 and 114:
Appendix C. Tests 102 Test 3 RCL 1
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Appendix C. Tests 116 160 140 120 1
Page 129 and 130:
Bibliography 118 [10] Michael R. Ga
show all

The Doctor Rostering Problem - Asser Fahrenholz

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?