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Identifying critical activities in stochastic resource constrained networks

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  • Bowers, J.

Abstract

The analysis of the stochastic project network can provide indications of both the magnitude of temporal risk and the sources of that risk. In a project dominated by technological dependencies rather than resource constraints, the sources of risk can be identified by examining the probabilities of each activity lying on a critical path. Similar criticality probabilities can also be derived for resource constrained stochastic networks if the definition of the critical path is revised. The use of this revised criticality probability is illustrated in an analysis of an example project and other possible measures of identifying the important activities are considered. A quantitative test of the value of the information provided by the criticality probability is developed and applied to a set of 100 randomly generated project networks, comparing the possible measures. This test indicates that the criticality probability provides valuable management information, extending the familiar concept of the critical path to the resource constrained stochastic network.

Suggested Citation

  • Bowers, J., 1996. "Identifying critical activities in stochastic resource constrained networks," Omega, Elsevier, vol. 24(1), pages 37-46, February.
  • Handle: RePEc:eee:jomega:v:24:y:1996:i:1:p:37-46
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    References listed on IDEAS

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    1. Christofides, Nicos & Alvarez-Valdes, R. & Tamarit, J. M., 1987. "Project scheduling with resource constraints: A branch and bound approach," European Journal of Operational Research, Elsevier, vol. 29(3), pages 262-273, June.
    2. Soroush, H. M., 1994. "The most critical path in a PERT network: A heuristic approach," European Journal of Operational Research, Elsevier, vol. 78(1), pages 93-105, October.
    3. Bajis M. Dodin & Salah E. Elmaghraby, 1985. "Approximating the Criticality Indices of the Activities in PERT Networks," Management Science, INFORMS, vol. 31(2), pages 207-223, February.
    4. E. Demeulemeester & B. Dodin & W. Herroelen, 1993. "A Random Activity Network Generator," Operations Research, INFORMS, vol. 41(5), pages 972-980, October.
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    2. Rabbani, M. & Fatemi Ghomi, S.M.T. & Jolai, F. & Lahiji, N.S., 2007. "A new heuristic for resource-constrained project scheduling in stochastic networks using critical chain concept," European Journal of Operational Research, Elsevier, vol. 176(2), pages 794-808, January.

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