Gutjahr, W. J.; Strauss, C.; Wagner, E. A stochastic branch-and-bound approach to activity crashing in project management. (English) Zbl 1034.90005 INFORMS J. Comput. 12, No. 2, 125-135 (2000). Summary: Many applications such as project scheduling, workflow modeling, or business process re-engineering incorporate the common idea that a product, task, or service consisting of interdependent time-related activities should be produced or performed within given time limits. In real-life applications, certain measures like the use of additional manpower, the assignment of highly-skilled personnel to specific jobs, or the substitution of equipment are often considered as means of increasing the probability of meeting a due date and thus avoiding penalty costs. This paper investigates the problem of selecting, from a set of possible measures of this kind, the combination of measures that is the most cost-efficient. Assuming stochastic activity durations, the computation of the optimal combination of measures may be very expensive in terms of runtime. In this article, we introduce a powerful stochastic optimization approach to determine a set of efficient measures that crash selected activities in a stochastic activity network. Our approach modifies the conventional stochastic branch-and-bound, using a heuristic – instead of exact methods – to solve the deterministic subproblem. This modification spares computational time and by doing so provides an appropriate method for solving various related applications of combinatorial stochastic optimization. A comparative computational study shows that our approach not only outperforms standard techniques but also definitely improves conventional stochastic branch-and-bound. Cited in 24 Documents MSC: 90B50 Management decision making, including multiple objectives 90C55 Methods of successive quadratic programming type 90C15 Stochastic programming PDFBibTeX XMLCite \textit{W. J. Gutjahr} et al., INFORMS J. Comput. 12, No. 2, 125--135 (2000; Zbl 1034.90005) Full Text: DOI Link