abstract = "Globally, power projects are prone to cost overrun
projects. Within the body of knowledge, previous
studies have paid less attention to predicting the cost
overruns to assist contingency cost planning.
Particularly, in thermal power plant projects (TPPPs),
the enormous risks involved in their delivery undermine
the accuracy of cost overrun prediction. To prevent
cost overrun in thermal power plant projects, these
risks need to be accounted for by employing
sophisticated cost overrun prediction techniques. This
study aims to develop a hybrid
predictive-probabilistic-based model (HPPM) that
integrates a genetic programming technique with Monte
Carlo simulation (MCS). The HPPM was proposed based on
the data collected from TPPPs in Bangladesh. Also, the
sensitivity of the HPPM was examined to identify the
critical risks in cost overruns simulation. The
simulation outcomes show that 40.48percent of a
projects initial estimated budget was the most probable
to cost overrun, while the maximum cost overrun will
not exceed 75percent with 90percent confidence.
Practically, the analysis will sensitize project
managers to emphasize thermal plants budget accuracy
not only at the initial project delivery phase but
throughout the project life cycle. Theoretically, the
HPPM could be employed for cost overrun prediction in
other types of power plant projects.",
notes = "School of Engineering and Technology, Central
Queensland Univ., Melbourne Campus, VIC3000,
Australia.