Due to the practical importance of stochastic project networks
(PERT-networks), many methods have been developed over the past
decades in order to obtain information about the random project
completion time. Of particular interest are methods that provide
(lower and upper) bounds for its distribution, since these aim at
balancing efficiency of calculation with accuracy of the obtained
information.
We provide a thorough computational evaluation of the most promising
of these bounding algorithms with the aim to test their suitability
for practical applications both in terms of efficiency and quality.
To this end, we have implemented these algorithms and compare their
behavior on a basis of nearly 2000 instances with up to 1200
activities of different test-sets. These implementations are based
on a suitable numerical representation of distributions which is the
basis for excellent computational results. Particularly a
distribution-free heuristic based on the Central Limit Theorem
provides an excellent tool to evaluate stochastic project networks.
