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Evaluating Project Scheduling and Due Date Assignment Procedures: An Experimental Analysis

Author

Listed:
  • John Dumond

    (Air Force Institute of Technology, Wright-Patterson Air Force Base, Dayton, Ohio 45402)

  • Vincent A. Mabert

    (School of Business, Indiana University, Bloomington, Indiana 47405)

Abstract

Managers of construction projects, maintenance activities, auditing contracts, software shops, etc. are frequently faced with the task of establishing a new project's due date, which must compete with other projects already in progress or expected (forecasted) to start in the future. The study reported here addresses the problem of establishing due dates for projects which require limited resources, in an environment where new projects arrive continuously and randomly over time. A set of procedures is developed which set each project's due date when it arrives using information about the new project, current projects, and available resources. The due date setting procedures are tested via simulation with four activity scheduling heuristics that control the assignment of resources to specific activities of available projects. A second test demonstrates the performance of the due date procedures, where a portion of arriving projects have their due dates established by external forces beyond management's control. Performance measures of project mean completion time, project mean lateness, project standard deviation of lateness, and total tardiness (sum of all projects' tardy time) were collected for evaluation. This study presents a number of important results for managers interested in scheduling projects and setting due dates. First, using more information concerning the current work in progress, available resources, and activity precedent relationships provides a better due date estimate for a new project. Second, a finite scheduling procedure (called SFT) consistently gives better due date estimates than simpler aggregate procedures. Third, when some project due dates are set externally, due date performance deteriorates. However, when SFT is combined with a due date oriented activity scheduling rule, due dale performance deterioration is less. Fourth, the effort, measured by CPU time, for SFT to estimate a good due date depends upon the ratio of activity resources required to total resources available, rather than the number of activities across all projects. And fifth, similarities and differences between the results observed in this study and past due date job shop scheduling research are reviewed.

Suggested Citation

  • John Dumond & Vincent A. Mabert, 1988. "Evaluating Project Scheduling and Due Date Assignment Procedures: An Experimental Analysis," Management Science, INFORMS, vol. 34(1), pages 101-118, January.
    • Handle: RePEc:inm:ormnsc:v:34:y:1988:i:1:p:101-118
    DOI: 10.1287/mnsc.34.1.101
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    Citations

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    Cited by:

    1. Viana, Ana & Pinho de Sousa, Jorge, 2000. "Using metaheuristics in multiobjective resource constrained project scheduling," European Journal of Operational Research, Elsevier, vol. 120(2), pages 359-374, January.
    2. Goswami, Indranil & Urminsky, Oleg, 2021. "Don’t fear the meter: How longer time limits bias managers to prefer hiring with flat fee compensation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 162(C), pages 42-58.
    3. Lova, Antonio & Maroto, Concepcion & Tormos, Pilar, 2000. "A multicriteria heuristic method to improve resource allocation in multiproject scheduling," European Journal of Operational Research, Elsevier, vol. 127(2), pages 408-424, December.
    4. Yang, Kum-Khiong & Sum, Chee-Chuong, 1997. "An evaluation of due date, resource allocation, project release, and activity scheduling rules in a multiproject environment," European Journal of Operational Research, Elsevier, vol. 103(1), pages 139-154, November.
    5. Song, D. P. & Hicks, C. & Earl, C. F., 2002. "Product due date assignment for complex assemblies," International Journal of Production Economics, Elsevier, vol. 76(3), pages 243-256, April.
    6. M. Suresh & Pankaj Dutta & Karuna Jain, 2015. "Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-30, December.
    7. Bredael, Dries & Vanhoucke, Mario, 2023. "Multi-project scheduling: A benchmark analysis of metaheuristic algorithms on various optimisation criteria and due dates," European Journal of Operational Research, Elsevier, vol. 308(1), pages 54-75.
    8. Philipp Melchiors & Rainer Kolisch & John J. Kanet, 2024. "The performance of priority rules for the dynamic stochastic resource-constrained multi-project scheduling problem: an experimental investigation," Annals of Operations Research, Springer, vol. 338(1), pages 569-595, July.
    9. Thomas Schmitt & Bruce Faaland, 2004. "Scheduling recurrent construction," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(8), pages 1102-1128, December.
    10. Krüger, Doreen & Scholl, Armin, 2009. "A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times," European Journal of Operational Research, Elsevier, vol. 197(2), pages 492-508, September.
    11. Hans, E.W. & Herroelen, W. & Leus, R. & Wullink, G., 2007. "A hierarchical approach to multi-project planning under uncertainty," Omega, Elsevier, vol. 35(5), pages 563-577, October.
    12. Shima Javanmard & Behrouz Afshar-Nadjafi & Seyed Taghi Akhavan Niaki, 2022. "A bi-objective model for scheduling of multiple projects under multi-skilled workforce for distributed load energy usage," Operational Research, Springer, vol. 22(3), pages 2245-2280, July.
    13. Gómez Sánchez, Mariam & Lalla-Ruiz, Eduardo & Fernández Gil, Alejandro & Castro, Carlos & Voß, Stefan, 2023. "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 309(3), pages 958-976.
    14. Browning, Tyson R. & Yassine, Ali A., 2010. "Resource-constrained multi-project scheduling: Priority rule performance revisited," International Journal of Production Economics, Elsevier, vol. 126(2), pages 212-228, August.
    15. Rob Eynde & Mario Vanhoucke, 2020. "Resource-constrained multi-project scheduling: benchmark datasets and decoupled scheduling," Journal of Scheduling, Springer, vol. 23(3), pages 301-325, June.
    16. He, Zesheng & Yang, Taeyong & Tiger, Andy, 1996. "An exchange heuristic imbedded with simulated annealing for due-dates job-shop scheduling," European Journal of Operational Research, Elsevier, vol. 91(1), pages 99-117, May.
    17. Gonçalves, J.F. & Mendes, J.J.M. & Resende, M.G.C., 2008. "A genetic algorithm for the resource constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1171-1190, September.
    18. Saeed Yaghoubi, 2015. "Due-date assignment for multi-server multi-stage assembly systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1246-1256, May.
    19. Azaron, Amir & Fynes, Brian & Modarres, Mohammad, 2011. "Due date assignment in repetitive projects," International Journal of Production Economics, Elsevier, vol. 129(1), pages 79-85, January.

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