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Optimum Time Compression in Project Scheduling

Author

Listed:
  • L. R. Lamberson

    (Department of Industrial Engineering, General Motors Institute)

  • R. R. Hocking

    (Institute of Statistics, Texas A & M University)

Abstract

An algorithm based on convex programming is developed for optimum time compression in network scheduling systems. The development allows for the activity time-cost trade-off functions to be any differentiable convex function. Decomposition theory is then applied to reduce the amount of computation necessary. This along with a limited number of rules to structure any incoming vector makes the algorithm amenable to time compression in large project networks.

Suggested Citation

  • L. R. Lamberson & R. R. Hocking, 1970. "Optimum Time Compression in Project Scheduling," Management Science, INFORMS, vol. 16(10), pages 597-606, June.
    • Handle: RePEc:inm:ormnsc:v:16:y:1970:i:10:p:b597-b606
    DOI: 10.1287/mnsc.16.10.B597
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    Citations

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    Cited by:

    1. Vanhoucke, Mario, 2005. "New computational results for the discrete time/cost trade-off problem with time-switch constraints," European Journal of Operational Research, Elsevier, vol. 165(2), pages 359-374, September.
    2. Helena Gaspars, 2006. "A conception of a new algorithm for the project time-cost analysis," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(3-4), pages 5-27.
    3. R L Bregman, 2009. "Preemptive expediting to improve project due date performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 120-129, January.
    4. Choi, Byung-Cheon & Park, Myoung-Ju, 2015. "A continuous time–cost tradeoff problem with multiple milestones and completely ordered jobs," European Journal of Operational Research, Elsevier, vol. 244(3), pages 748-752.
    5. Azaron, Amir & Katagiri, Hideki & Sakawa, Masatoshi & Kato, Kosuke & Memariani, Azizollah, 2006. "A multi-objective resource allocation problem in PERT networks," European Journal of Operational Research, Elsevier, vol. 172(3), pages 838-854, August.
    6. Yaghoubi, Saeed & Noori, Siamak & Azaron, Amir & Fynes, Brian, 2015. "Resource allocation in multi-class dynamic PERT networks with finite capacity," European Journal of Operational Research, Elsevier, vol. 247(3), pages 879-894.
    7. Bregman, Robert L., 2009. "A heuristic procedure for solving the dynamic probabilistic project expediting problem," European Journal of Operational Research, Elsevier, vol. 192(1), pages 125-137, January.
    8. Anton-Sanchez, Laura & Landete, Mercedes & Saldanha-da-Gama, Francisco, 2023. "The discrete p-center location problem with upgrading," Omega, Elsevier, vol. 119(C).
    9. Azaron, Amir & Tavakkoli-Moghaddam, Reza, 2007. "Multi-objective time-cost trade-off in dynamic PERT networks using an interactive approach," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1186-1200, August.
    10. M. Vanhoucke, 2007. "An electromagnetic time/cost trade-off optimization in project scheduling," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/457, Ghent University, Faculty of Economics and Business Administration.
    11. S. Selcuk Erenguc & Taeho Ahn & Daniel G. Conway, 2001. "The resource constrained project scheduling problem with multiple crashable modes: An exact solution method," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(2), pages 107-127, March.
    12. Nicole Megow & Rolf H. Möhring & Jens Schulz, 2011. "Decision Support and Optimization in Shutdown and Turnaround Scheduling," INFORMS Journal on Computing, INFORMS, vol. 23(2), pages 189-204, May.
    13. Ahn, Taeho & Erenguc, S. Selcuk, 1998. "The resource constrained project scheduling problem with multiple crashable modes: A heuristic procedure," European Journal of Operational Research, Elsevier, vol. 107(2), pages 250-259, June.

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