Integrated probabilistic schedules and estimates from project simulated data

roy J. Le Isidore, W. Edward Back and Gary Fry

Construction Management and Economics, 2001, vol. 19, issue 4, 417-426

Abstract: Risk management, as it relates to construction, is vital to the successful undertaking and completion of any construction project. One way to manage project risk effectively is to develop more reliable means of accounting for the time and cost variability existing in construction operations. Recent attempts to more reliably quantify the risk inherent in construction projects has focused on range estimating and stochastic scheduling (also referred to as probabilistic estimating and probabilistic scheduling). It is common knowledge in the construction industry that the cost associated with a project is affected greatly by the schedule selected to complete that project. Additionally, the percentile level associated with both of these tools is of significance when they are considered stochastically. This paper looks at the integration of range estimating and probabilistic scheduling, using a new procedure called the empirical cumulative density function technique (ECDF) as a means of further controlling the risk associated with the undertaking of construction projects. In addition to providing a reliable means of relating the results of range estimating and probabilistic scheduling, this technique is graphically based, and has the advantage of not requiring any assumptions regarding the underlying data distributions.

Keywords: Integrated Cost And Schedule Monte Carlo Simulation Range Estimating Probabilistic Estimating Probabilistic Scheduling (search for similar items in EconPapers)
Date: 2001
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/01446190010022677 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:conmgt:v:19:y:2001:i:4:p:417-426

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCME20

DOI: 10.1080/01446190010022677

Access Statistics for this article

Construction Management and Economics is currently edited by Will Hughes

More articles in Construction Management and Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().