Flexible Services and Manufacturing Journal

, Volume 28, Issue 4, pp 694–702 | Cite as

A note on the selection of priority rules in software packages for project management

  • Philipp Baumann
  • Norbert Trautmann


Various software packages for project management include a procedure for resource-constrained scheduling. In several packages, the user can influence this procedure by selecting a priority rule. However, the resource-allocation methods that are implemented in the procedures are proprietary information; therefore, the question of how the priority-rule selection impacts the performance of the procedures arises. We experimentally evaluate the resource-allocation methods of eight recent software packages using the 600 instances of the PSPLIB J120 test set. The results of our analysis indicate that applying the default rule tends to outperform a randomly selected rule, whereas applying two randomly selected rules tends to outperform the default rule. Applying a small set of more than two rules further improves the project durations considerably. However, a large number of rules must be applied to obtain the best possible project durations.


Project scheduling Software Priority rules Experimental analysis 


  1. Assad A, Wasil E (1986) Project management using a microcomputer. Compute Oper Res 13:231–260CrossRefGoogle Scholar
  2. Baumann P, Trautmann N (2015) Resource-constrained project scheduling with project management information systems. In: Schwindt C, Zimmermann J (eds) Handbook on project management and scheduling, vol 2., International handbooks on information systems. Springer, New york, pp 1385–1400Google Scholar
  3. Beşikci U, Bilge Ü, Gündüz U (2013) Resource dedication problem in a multi-project environment. Flex Serv Manuf J 25:206–229CrossRefGoogle Scholar
  4. Brucker P, Drexl A, Möhring R, Neumann K, Pesch E (1999) Resource-constrained project scheduling: notation, classification, models, and methods. Eur J Oper Res 112:3–41CrossRefMATHGoogle Scholar
  5. De Wit J, Herroelen W (1990) An evaluation of microcomputer-based software packages for project management. Eur J Oper Res 49:102–139CrossRefGoogle Scholar
  6. Fang C, Kolisch R, Wang L, Mu C (2015) An estimation of distribution algorithm and new computational results for the stochastic resource-constrained project scheduling problem. Flex Serv Manuf J 27:585–605CrossRefGoogle Scholar
  7. Farid F, Manoharan S (1996) Comparative analysis of resource allocation capabilities of project management software packages. Proj Manag J 27:35–44Google Scholar
  8. Hartmann S (2013) Project scheduling with resource capacities and requests varying with time: a case study. Flex Serv Manuf J 25:74–93CrossRefGoogle Scholar
  9. Herroelen W (2005) Project scheduling–theory and practice. Prod Oper Manag 14:413–432CrossRefGoogle Scholar
  10. Johnson R (1992) Resource constrained scheduling capabilities of commercial project management software. Proj Manag J 22:39–43Google Scholar
  11. Kastor A, Sirakoulis K (2009) The effectiveness of resource levelling tools for resource constraint project scheduling problem. Int J Proj Manag 27:493–500CrossRefGoogle Scholar
  12. Khattab M, Søyland K (1996) Limited resource allocation in construction projects. Comput Ind Eng 31:229–232CrossRefGoogle Scholar
  13. Klein R (2000) Scheduling of resource-constrained projects. Kluwer, BostonCrossRefMATHGoogle Scholar
  14. Kolisch R (1999) Resource allocation capabilities of commercial project management software packages. Interfaces 29(4):19–31CrossRefGoogle Scholar
  15. Kolisch R, Hempel K (1996) Experimentelle Evaluation der Kapazitätsplanung von Projektmanagementsoftware. Zeitschrift für betriebswirtschaftliche Forschung 48:999–1018Google Scholar
  16. Kolisch R, Sprecher A (1997) PSPLIB—a project scheduling problem library. Eur J Oper Res 96:205–216CrossRefMATHGoogle Scholar
  17. Liberatore M, Pollack-Johnson B (2003) Factors influencing the usage and selection of project management software. IEEE Trans Eng Manag 50:164–174CrossRefGoogle Scholar
  18. Maroto C, Tormos P (1994) Project management: an evaluation of software quality. Int Trans Oper Res 1:209–221CrossRefGoogle Scholar
  19. Mellentien C, Trautmann N (2001) Resource allocation with project management software. OR Spectr 23:383–394MathSciNetCrossRefMATHGoogle Scholar
  20. Trautmann N, Baumann P (2009a) Project scheduling with precedence constraints and scarce resources: an experimental analysis of commercial project management software. In: Fleischmann B, Borgwardt KH, Klein R, Tuma A (eds) Operations research proceedings 2008, vol 2008. Springer, Berlin, pp 165–170CrossRefGoogle Scholar
  21. Trautmann N, Baumann P (2009b) Resource-allocation capabilities of commercial project management software: an experimental analysis. In: International conference on computers & industrial engineering, CIE 2009, IEEE, pp 1143–1148Google Scholar
  22. White D, Fortune J (2002) Current practice in project management—an empirical study. Int J Proj Manag 20:1–11CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.University of BernBernSwitzerland

Personalised recommendations