Journal of Scheduling

, Volume 11, Issue 2, pp 137–148 | Cite as

Time-constrained project scheduling

  • T. A. Guldemond
  • J. L. Hurink
  • J. J. Paulus
  • J. M. J. Schutten
Open Access
Article

Abstract

We propose a new approach for scheduling with strict deadlines and apply this approach to the Time-Constrained Project Scheduling Problem (TCPSP). To be able to meet these deadlines, it is possible to work in overtime or hire additional capacity in regular time or overtime. For this problem, we develop a two stage heuristic. The key of the approach lies in the first stage in which we construct partial schedules. In these partial schedules, jobs may be scheduled for a shorter duration than required. The second stage uses an ILP formulation of the problem to turn a partial schedule into a feasible schedule, and to perform a neighborhood search. The developed heuristic is quite flexible and, therefore, suitable for practice. We present experimental results on modified RCPSP benchmark instances. The two stage heuristic solves many instances to optimality, and if we substantially decrease the deadline, the rise in cost is only small.

Keywords

Project scheduling Strict deadlines 

References

  1. Deckro, R. F., & Herbert, J. E. (1989). Resource constrained project crashing. OMEGA International Journal of Management Science, 17, 69–79. CrossRefGoogle Scholar
  2. Demeulemeester, E. (1995). Minimizing resource availability costs in time-limited project networks. Management Science, 41(10), 1590–1598. Google Scholar
  3. Demeulemeester, E., & Herroelen, W. (1997). New benchmark results for the resource-constrained project scheduling problem. Management Science, 43, 1485–1492. Google Scholar
  4. Gademann, N., & Schutten, M. (2005). Linear-programming-based heuristics for project capacity planning. IIE Transactions, 37, 153–165. CrossRefGoogle Scholar
  5. Guldemond, T. A., Hurink, J. L., Paulus, J. J., & Schutten, J. M. J. (2006). Time-constrained project scheduling; details of the computational tests. http://tcpsp.ewi.utwente.nl/.
  6. Herroelen, W., De Reyck, B., & Demeulemeester, E. (1998). Resource-constrained project scheduling: a survey of recent developments. Computers and Operations Research, 25, 279–302. CrossRefGoogle Scholar
  7. Kis, T. (2005). A branch-and-cut algorithm for scheduling of projects with variable intensity activities. Mathematical Programming, 103, 515–539. CrossRefGoogle Scholar
  8. Kolisch, R. (1995). Project scheduling under resource constraints. Berlin: Physica. Google Scholar
  9. Kolisch, R., & Drexl, A. (1996). Adaptive search for solving hard project scheduling problems. Naval Research Logistics, 43, 23–40. CrossRefGoogle Scholar
  10. Kolisch, R., & Hartmann, S. (1999). Heuristic algorithms for solving the resource-constrained project scheduling problem: classification and computational analysis. In J. Weglarz (Ed.), Handbook on recent advances in project scheduling (pp. 197–212). Dordrecht: Kluwer. Google Scholar
  11. Kolisch, R., & Padman, R. (2001). An integrated survey of deterministic project scheduling. Omega, 29, 249–272. CrossRefGoogle Scholar
  12. Kolisch, R., & Sprecher, A. (1997a). Project scheduling library—PSPlib. http://129.187.106.231/psplib/.
  13. Kolisch, R., & Sprecher, A. (1997b). PSPLIB a project scheduling problem library. European Journal of Operational Research, 96, 205–216. CrossRefGoogle Scholar
  14. Kolisch, R., Sprecher, A., & Drexl, A. (1995). Characterization and generation of a general class of resource-constrained project scheduling problems. Management Science, 41(10), 1693–1703. CrossRefGoogle Scholar
  15. Li, R. K.-Y., & Willis, R. J. (1993). Resource constrained scheduling within fixed project durations. The Journal of the Operational Research Society, 44, 71–80. CrossRefGoogle Scholar
  16. Möhring, R. H. (1984). Minimizing costs of resource requirements in project networks subject to a fixed completion time. Operations Research, 32(1), 89–120. Google Scholar
  17. Neumann, K., Schwindt, C., & Zimmermann, J. (2002). Project scheduling with time windows and scarce resources. Lecture notes in economics and mathematical systems (Vol. 508). Berlin: Springer. Google Scholar
  18. Palpant, M., Artigues, C., & Michelon, P. (2004). LSSPER: solving the resource-constrained project scheduling problem with large neighbourhood search. Annals of Operations Research, 131, 237–257. CrossRefGoogle Scholar

Copyright information

© The Author(s) 2008

Authors and Affiliations

  • T. A. Guldemond
    • 1
  • J. L. Hurink
    • 2
  • J. J. Paulus
    • 2
  • J. M. J. Schutten
    • 2
  1. 1.ORTEC bvAL, GoudaThe Netherlands
  2. 2.University of TwenteAE, EnschedeThe Netherlands

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