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Using the generalized maximum covering location model to control a project’s progress

Author

Listed:
  • Narjes Sabeghi

    (Velayat University
    Ferdowsi University of Mashhad)

  • Hamed Reza Tareghian

    (Ferdowsi University of Mashhad)

Abstract

Project control consists of monitoring a project’s progress at so called control points, finding possible deviations from the baseline schedule and if necessary, making adjustments to the deviated schedule subject to the available control budget, the adjusting strategies and also other technical and environmental possibilities in order to bring the schedule back on the right track. In this study, we adapt for the first time the generalized maximum covering location model to determine the adjusting strategies such that the maximum control coverage is achieved, i.e. under the given constraints, a schedule that is globally as close to the baseline schedule as possible is obtained. Numerical examples are given to illustrate the intricacies of the proposed method and also to demonstrate its applicability.

Suggested Citation

  • Narjes Sabeghi & Hamed Reza Tareghian, 2020. "Using the generalized maximum covering location model to control a project’s progress," Computational Management Science, Springer, vol. 17(1), pages 1-21, January.
    • Handle: RePEc:spr:comgts:v:17:y:2020:i:1:d:10.1007_s10287-018-0301-5
    DOI: 10.1007/s10287-018-0301-5
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    References listed on IDEAS

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    1. G Zhu & J F Bard & G Yu, 2005. "Disruption management for resource-constrained project scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(4), pages 365-381, April.
    2. Aytug, Haldun & Lawley, Mark A. & McKay, Kenneth & Mohan, Shantha & Uzsoy, Reha, 2005. "Executing production schedules in the face of uncertainties: A review and some future directions," European Journal of Operational Research, Elsevier, vol. 161(1), pages 86-110, February.
    3. Michael T. Pich & Christoph H. Loch & Arnoud De Meyer, 2002. "On Uncertainty, Ambiguity, and Complexity in Project Management," Management Science, INFORMS, vol. 48(8), pages 1008-1023, August.
    4. Berman, Oded & Krass, Dmitry & Drezner, Zvi, 2003. "The gradual covering decay location problem on a network," European Journal of Operational Research, Elsevier, vol. 151(3), pages 474-480, December.
    5. Zvi Drezner & George O. Wesolowsky & Tammy Drezner, 2004. "The gradual covering problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(6), pages 841-855, September.
    6. Raz, Tzvi & Erel, Erdal, 2000. "Optimal timing of project control points," European Journal of Operational Research, Elsevier, vol. 127(2), pages 252-261, December.
    7. Golenko-Ginzburg, Dimitri & Laslo, Zohar, 2001. "Timing control points via simulation for production systems under random disturbances," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(6), pages 451-458.
    8. Vanhoucke, Mario, 2011. "On the dynamic use of project performance and schedule risk information during projecttracking," Omega, Elsevier, vol. 39(4), pages 416-426, August.
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