Chance-constrained programming in activity networks: A critical evaluation

Salah E. Elmaghraby*, Hanijanto Soewandi, Ming-Jong Yao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We review the chance-constrained programming (CCP) model for event realization in activity networks (ANs), and the more recent contribution to it by Kress, from the points of view of validity and accuracy. We present a classification scheme of stochastic programming and confirm that the CCP does not solve the problem of finding a point estimate that satisfies a required confidence level, and is of little help in determining the cumulative distribution function (c.d.f.) of the project completion time. We show that the CCP leads to an extremely weak lower bound (l.b.) on the exact c.d.f. A backtracking approach is proposed that improves this l.b. via the CCP, which is still too weak to be of any practical value. Finally, we utilize the CCP approach to derive a result due to Kress in a simpler and more direct way. We also demonstrate that the result itself, unfortunately, is of questionable validity.

Original languageEnglish
Pages (from-to)440-458
Number of pages19
JournalEuropean Journal of Operational Research
Issue number2
StatePublished - 1 Jun 2001


  • Activity networks
  • Chance-constrained programming

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