OR Spectrum

, Volume 32, Issue 2, pp 343–368 | Cite as

Scheduling and staffing multiple projects with a multi-skilled workforce

Regular Article

Abstract

We consider the problem of simultaneously scheduling IT-projects and assigning multi-skilled internal and external human resources with resource-specific efficiencies to the project work. The objective is to minimize labor costs. The problem is modeled as a mixed-integer linear program (MIP) with a tight LP-bound. The performance of the model w.r.t. solution gap and computation time is assessed and managerial insight is given concerning different problem parameters such as the time window size of projects, the number of skills of human resources, and the workload. Furthermore, we show the benefit of applying the MIP compared to simple heuristics used in practice in terms of obtaining feasible and low-cost solutions. Finally, we provide insight into the benefit of applying the MIP in case of central compared to decentral planning.

Keywords

Project scheduling Project staffing Resource assignment Multi-skilled resources Heterogeneous efficiencies 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alba E, Chicano FJ (2007) Software project management with GAs. Inf Sci 177(11): 2380–2401CrossRefGoogle Scholar
  2. Alfares H, Bailey J (1997) Integrated project task and manpower scheduling. IIE Trans 29(9): 711–717Google Scholar
  3. Ballou D, Tayi G (1996) A decision aid for the selection and scheduling of software maintenance projects. IEEE Trans Syst Man Cybern Part A Syst Hum 26(2): 203–212CrossRefGoogle Scholar
  4. Bassett M (2000) Assigning projects to optimize the utilization of employees’ time and expertise. Comput Chem Eng 24(2–7): 1013–1021CrossRefGoogle Scholar
  5. Bellenguez-Morineau O, Néron E (2007) A branch-and-bound method for solving multi-skill project scheduling problem. RAIRO Oper Res 41(2): 155–170CrossRefGoogle Scholar
  6. Brucker P, Drexl A, Möhring R, Neumann K, Pesch E (1999) Resource-constrained project scheduling: notation, classification, models, and methods. Eur J Oper Res 112(1): 3–41CrossRefGoogle Scholar
  7. Cai X, Li K (2000) A genetic algorithm for scheduling staff of mixed skills under multi-criteria. Eur J Oper Res 125(2): 359–369CrossRefGoogle Scholar
  8. Campbell G (1999) Cross-utilization of workers whose capabilities differ. Manage Sci 45(5): 722–732CrossRefGoogle Scholar
  9. Campbell G, Diaby M (2002) Development and evaluation of an assignment heuristic for allocating cross-trained workers. Eur J Oper Res 138(1): 9–20CrossRefGoogle Scholar
  10. Corominas A, Ojeda J, Pastor R (2005) Multi-objective allocation of multi-function workers with lower bounded capacity. J Oper Res Soc 56(6): 738–743CrossRefGoogle Scholar
  11. Corominas A, Pastor R, Rodriguez E (2006) Rotational allocation of tasks to multifunctional workers in a service industry. Int J Prod Econ 103(1): 3–9CrossRefGoogle Scholar
  12. Dodin B, Elimam A (1997) Audit scheduling with overlapping activities and sequence-dependent setup costs. Eur J Oper Res 97(1): 22–33CrossRefGoogle Scholar
  13. Drexl A (1991) Scheduling of project networks by job assignment. Manage Sci 37(12): 1590–1602CrossRefGoogle Scholar
  14. Ernst A, Jiang H, Krishamoorthy M, Sier D (2004) Staff scheduling and rostering: a review of applications, methods and models. Eur J Oper Res 153(1): 3–27CrossRefGoogle Scholar
  15. Garey M, Johnson D (1979) Computers and intractability—a guide to the theory of NP-completeness. W.H. Freeman, New YorkGoogle Scholar
  16. Gutjahr WJ, Reiter P (2008) Bi-objective project portfolio selection and staff assignment under uncertainty. Technical report, Universität WienGoogle Scholar
  17. Gutjahr W, Katzensteiner S, Reiter P, Stummer C, Denk M (2008a) Competence-driven project portfolio selection, scheduling and staff assignment. Cent Eur J Oper Res 16(3): 281–306CrossRefGoogle Scholar
  18. Gutjahr WJ, Katzensteiner S, Reiter P, Stummer C, Denk M (2008b) Multi-objective decision analysis for competence-oriented project portfolio selection. Technical report, Universität WienGoogle Scholar
  19. Taylor B, Moore L, Clayton E (1982) R&D project selection and manpower allocation with integer nonlinear goal programming. Manage Sci 28(10): 1149–1158CrossRefGoogle Scholar
  20. Vairaktarakis G (2003) The value of resource flexibility in the resource-constrained job assignment problem. Manage Sci 49(6): 718–732CrossRefGoogle Scholar
  21. Valls V, Pérez A, Quintanilla S (1996) A graph colouring model for assigning a heterogeneous workforce to a given schedule. Eur J Oper Res 90(2): 285–302CrossRefGoogle Scholar
  22. Valls V, Pérez A, Quintanilla S (2009) Skilled workforce scheduling in service centers. Eur J Oper Res 193(3): 791–804CrossRefGoogle Scholar
  23. Wu M-C, Sun S-H (2006) A project scheduling and staff assignment model considering learning effect. Int J Adv Manuf Technol 28(11–12): 1190–1195CrossRefGoogle Scholar
  24. Yoshimura M, Fujimi Y, Izui K, Nishiwaki S (2006) Decision-making support system for human resource allocation in product development projects. Int J Prod Res 44(5): 831–848CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.TUM Business SchoolTechnische Universität MünchenMunichGermany

Personalised recommendations