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Annals of Computer Science and Information Systems, Volume 21

Proceedings of the 2020 Federated Conference on Computer Science and Information Systems

A Simulation Study on the Impact of Activity Crashing on the Project Duration and Cost under Different Budget Release Scenarios

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DOI: http://dx.doi.org/10.15439/2020F98

Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 603606 ()

Full text

Abstract. The main goal of project control is to identify project opportunities or problems during project execution, such that corrective actions can be taken to bring the project in danger back on track when necessary. In this study, we define different scenarios to allocate the limited budget used for the cost of activity execution, delays, and corrective actions, according to the timing and amount of the budget release. A large computational experiment is conducted on real-life project data to evaluate the performance of each scenario. The results show that both the timing and amount of the budget release have an effect on project performance.

References

  1. M. Vanhoucke, Project Management with Dynamic Scheduling: Baseline Scheduling, Risk Analysis and Project Control. Springer, 2012, vol. XVIII.
  2. Q. Fleming and J. Koppelman, Earned Value Project Management, 3rd ed. Newton Square, Pennsylvania: Project Management Institute, 2010. [Online]. Available: http://books.google.be/books?id=ZMRVngEACAAJ
  3. J. Colin and M. Vanhoucke, “Setting tolerance limits for statistical project control using earned value management,” Omega The International Journal of Management Science, vol. 49, pp. 107–122, 2014.
  4. A. Martens and M. Vanhoucke, “A buffer control method for top-down project control,” European Journal Of Operational Research, vol. 262, pp. 274–286, 2017.
  5. J. Zhang, S. Jia, and E. Diaz, “Dynamic monitoring and control of a critical chain project based on phase buffer allocation,” Journal of the Operational Research Society, vol. 69, pp. 1–12, 2018.
  6. H. Hadian and A. Rahimifard, “Multivariate statistical control chart and process capability indices for simultaneous monitoring of project duration and cost,” Computers & Industrial Engineering, pp. 788–797, 2019.
  7. M. Madadi and H. Iranmanesh, “A management oriented approach to reduce a project duration and its risk (variability),” European Journal of Operational Research, vol. 219, no. 3, pp. 751–761, 2012.
  8. P. Ballesteros-Pérez, K. Elamrousy, and M. Gonz’ales-Cruz, “Non-linear time-cost trade-off models of activity crashing: Application to construction scheduling and project compression with fast-tracking,” Automation in Construction, vol. 97, pp. 229–240, 2019.
  9. A. Martens and M. Vanhoucke, “The impact of applying effort to reduce activity uncertainty on the project time and cost performance,” European Journal of Operational Research, vol. 277, no. 2, pp. 442–453, 2019.
  10. J. Song, A. Martens, and M. Vanhoucke, “The impact of a limited budget on the corrective action taking process,” European Journal Of Operational Research, vol. 286, no. 3, pp. 1070–1086, 2020.
  11. M. Vanhoucke, A. Vereecke, and P. Gemmel, “The project scheduling game (PSG): Simulating time/cost trade-offs in projects,” Project Management Journal, vol. 51, pp. 51–59, 2005.
  12. J. Batselier and M. Vanhoucke, “Construction and evaluation framework for a real-life project database,” International Journal of Project Management, vol. 33, pp. 697–710, 2015.