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Health Care Management Science

, Volume 7, Issue 4, pp 305–317 | Cite as

Development of a Decision Support Model for Scheduling Clinical Studies and Assigning Medical Personnel

  • Martin Grunow
  • Hans-Otto GüntherEmail author
  • Gang Yang
Article

Abstract

Clinical studies for the development of new drugs in the pharmaceutical industry consist of a number of individual tasks which have to be carried out in a pre-defined chronological order. Each task requires certain types of medical personnel. This paper investigates the scheduling of clinical studies to be performed during a short-term planning horizon, the allocation of workforce between the studies, and the assignment of individual employees to tasks. Instead of developing a complex monolithic decision model, a hierarchical modelling approach is suggested. In the first stage, a compact integer optimization model is solved in order to determine the start-off times of the studies and the required staffing while taking the limited availability of personnel into account. The objective is to minimize total staffing costs. The assignment of individual employees to tasks is then made in the second stage of the procedure using a binary optimization model.

Keywords

personnel scheduling task assignment clinical studies pharmaceutical industry optimization model 

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References

  1. [1]
    K.A. Dowsland, Nurse scheduling with tabu search and strategic oscillation, European Journal of Operational Research 106 (1998) 393–407. Google Scholar
  2. [2]
    I. Berrada, J.A. Ferland and P. Michelon, A multi-objective approach to nurse scheduling with both hard and soft constraints, Socio-Econ. Plann. Sci. 30 (1996) 183–193. Google Scholar
  3. [3]
    B. Jaumard, F. Semet and T. Vovor, A generalized linear programming model for nurse scheduling, European Journal of Operational Research 107 (1998) 1–18. Google Scholar
  4. [4]
    S.P. Siferd, A decision model for shift scheduling of nurses, European Journal of Operational Research 74 (1994) 519–527. Google Scholar
  5. [5]
    F.F. Easton, D.F. Rossin and W.S. Borders, Analysis of alternative scheduling policies for hospital nurses, Production and Operations Management 1 (1992) 159–174. CrossRefGoogle Scholar
  6. [6]
    R. Burns, Personnel Scheduling, in: Handbook of Industrial Engineering, ed. G. Salvendy (Wiley, New York, 2001) pp. 1741–1767. Google Scholar
  7. [7]
    N. Beaumont, Scheduling staff using mixed-integer programming, European Journal of Operational Research 98 (1997) 473–484. Google Scholar
  8. [8]
    S.C. Sarin and S. Aggarwal, Modeling and algorithmic development of a staff scheduling problem, European Journal of Operational Research 128 (2001) 558–569. Google Scholar
  9. [9]
    J.F. Bard, C. Binici and A.H. deSilva, Staff scheduling at the United States Postal Service, Computers & Operations Research 30 (2003) 745–771. Google Scholar
  10. [10]
    G.B. Dantzig, A comment on Edie’s “Traffic delays at toll booths”, Journal of the Operations Research Society of America 2 (1954) 339–341. Google Scholar
  11. [11]
    K.R. Baker, Scheduling a full-time workforce to meet cyclic staffing requirements, Management Science 20 (1974) 1561–1568. Google Scholar
  12. [12]
    K.R. Baker and M.J. Magazine, Workforce scheduling with cyclic demands and day-off constraints, Management Science 24 (1977) 161–167. Google Scholar
  13. [13]
    H.K. Alfares, Efficient optimization of cyclic labor days-off scheduling, OR Spectrum 23 (2001) 283–294. Google Scholar
  14. [14]
    H.K. Alfares, Flexible 4-day workweek scheduling with weekend work frequency constraints, Computers and Industrial Engineering 44 (2003) 325–338. Google Scholar
  15. [15]
    J.G. Morris and M.J. Showalter, Simple approaches to shift, days-off and tour scheduling problems, Management Science 29 (1983) 942–950. Google Scholar
  16. [16]
    S.E. Bechtold and L.W. Jacobs, Implicit modeling of flexible break assignments in optimal shift scheduling, Management Science 36 (1990) 1339–1351. Google Scholar
  17. [17]
    G.M. Thompson, Improved implicit optimal modeling of the labor shift scheduling problem, Management Science 41 (1995) 595–607. Google Scholar
  18. [18]
    R.N. Burns and M.W. Carter, Work force size and single shift schedules with variable demands, Management Science 31 (1985) 599–607. Google Scholar
  19. [19]
    R.N. Burns and G.J. Koop, A modular approach to optimal multiple-shift manpower scheduling, Operations Research 35 (1987) 100–110. CrossRefGoogle Scholar
  20. [20]
    F.F. Easton and D.F. Rossin, Sufficient working subsets for the tour scheduling problem, Management Science 37 (1991) 1441–1451. Google Scholar
  21. [21]
    A.Z. Jarrah, J.F. Bard and A.H. deSilva, Solving large-scale tour scheduling problems, Management Science 40 (1994) 1124–1144. Google Scholar
  22. [22]
    S.E. Bechtold, M.J. Brusco and J. Showalter, A comparative evaluation of labor tour scheduling methods, Decision Sciences 22 (1991) 683–699. Google Scholar
  23. [23]
    H. Emmons and R.N. Burns, Off-day scheduling with hierarchical worker categories, Operations Research 39 (1991) 484–495. Google Scholar
  24. [24]
    A. Billionnet, Integer programming to schedule a hierarchical workforce with variable demands, European Journal of Operational Research 114 (1999) 105–114. Google Scholar
  25. [25]
    R. Hung, Single-shift day-off scheduling of hierarchical workforce with variable demands, European Journal of Operational Research 78 (1994) 49–57. Google Scholar
  26. [26]
    R. Narasimhan, An algorithm for single-shift scheduling of hierarchical workforce, European Journal of Operational Research 96 (1997) 113–121. Google Scholar
  27. [27]
    X. Cai and K.N. Li, A genetic algorithm for scheduling staff of mixed skills under multi-criteria, European Journal of Operational Research 125 (2000) 359–369. Google Scholar
  28. [28]
    I. Toroslu, Personnel assignment problem with hierarchical ordering constraints, Computers and Industrial Engineering 45 (2003) 493–510. Google Scholar
  29. [29]
    M. Pinedo, Workforce Scheduling, in: Planning and Scheduling in Manufacturing and Services, (Springer, Berlin, 2004) Ch. 12. Google Scholar
  30. [30]
    M. Grunow, H.-O. Günther and M. Lehmann, Campaign planning for multi-stage batch processes in the chemical industry, OR Spectrum 24 (2002) 281–314. Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  1. 1.Department of Production ManagementTechnical University BerlinBerlinGermany

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