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2023 | z. 186 W kierunku przyszłości zarządzania | 729--738
Tytuł artykułu

Monte Carlo Simulation Analysis of the Pert Method for Complete Graph with All Activities as Critical

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: The main objective of this study is to conduct a time analysis on a complete PERT network in a situation where all activities in the network are critical. This analysis is more exploratory and theoretical in nature, as it assumes a very specific case of a project and the potential implications arising from it. Design/methodology/approach: The analysis was performed on the full PERT network including 6 events and the resulting number of 15 activities. The numerical procedure was carried out by: determining the number of events and parameters of the project duration, determining the (maximum) number of activities - determining the parameters of the distribution of activity durations using mathematical programming, determining the number of iterations, in each iteration: generating activity durations, determining critical paths, determining time duration of the project and analysis of the results obtained. Findings: The work draws three main conclusions: the distribution of the project duration differs significantly from the theoretical PERT time, the theoretical activity durations affect the critical importance of activities in the project implementation, the number of events in the critical path affects the project implementation deadline. Research limitations/implications: The obtained results depend on the adopted methodology, in particular the numerical procedure for generating times: optimistic, modal, pessimistic of activities and generating activity durations from a normal distribution. Further research will focus on these issues. Originality/value: the main novelty of the work is the analysis using Monte Carlo simulation on the full PERT network, where all activities are critical. (original abstract)
Twórcy
autor
  • Silesian University of Technology
Bibliografia
  • 1. Cook, D.L. (1966). Program evaluation and review technique: Applications in education (No. 17). US Department of health, education, and welfare. Office of education.
  • 2. Deshmukh, P., Rajhans, N.R. (2018). Comparison of project scheduling techniques: PERT versus Monte Carlo simulation. Industrial Engineering Journal, 11(7).
  • 3. Dodin, B. (1984). Determining the K most critical paths in PERT networks. Operations Research, 32(4), 859-877.
  • 4. Karabulut, M. (2017). Application of Monte Carlo simulation and PERT/CPM techniques in planning of construction projects: A Case Study. Periodicals of Engineering and Natural Sciences, 5(3).
  • 5. Lu, M., AbouRizk, S.M. (2000). Simplified CPM/PERT simulation model. Journal of Construction Engineering and Management, 126(3), 219-226.
  • 6. Malcolm, D., Roseboom, J., Clark, C., Fazar, W. (1959). Application of a technique for research and development program evaluation. Operations Research, 7, 646-669.
  • 7. R Core Team (2022). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
  • 8. Salas-Morera, L., Arauzo-Azofra, A., García-Hernández, L., Palomo-Romero, J.M., Ayuso- Muñoz, J.L. (2018). New approach to the distribution of project completion time in pert networks. Journal of Construction Engineering and Management, 144(10), 04018094.
  • 9. Schonberger, R.J. (1981). Why projects are "always" late: a rationale based on manual simulation of a PERT/CPM network. Interfaces, 11(5), 66-70.
  • 10. Soroush, H.M. (1994). The most critical path in a PERT network. Journal of the Operational Research Society, 45, 287-300.
  • 11. Trocki, M., Grucza, B., Ogonek, K. (2011). Zarządzanie projektami. PWE.
  • 12. Udoumoh, E.F., Ebong, D.W. (2017). A review of activity time distributions in risk analysis. American Journal of Operations Research, 7(06), 356.
  • 13. United States. Bureau of Naval Weapons. Special Projects Office (1958). Program Evaluation Research Task (PERT): Summary Report. Phase 2. Special Projects Office, Bureau of Naval Weapons, Department of the Navy. Government Printing.
  • 14. Van Slyke, R.M. (1963). Monte Carlo methods and the PERT problem. Operations Research, 11(5), 839-860.
  • 15. Walczak, R. (2014). Analiza ryzyka harmonogramowania projektu z wykorzystaniem metody Monte Carlo. Innowacje w zarządzaniu i inżynierii produkcji. R. Knosala (ed.). Opole: Oficyna Wydawnicza Polskiego Towarzystwa Zarządzania Produkcją, 914-925.
  • 16. Wyrozębski, P., Wyrozębska, A. (2013). Challenges of project planning in the probabilistic approach using PERT, GERT and Monte Carlo. Journal of Management and Marketing, 2013 November 30.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171690352

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