Project's duration prediction: Traditional tools or simulation?

Diamantas, VK; Kirytopoulos, KA; Leopoulos, VN

dc.contributor.author	Diamantas, VK	en
dc.contributor.author	Kirytopoulos, KA	en
dc.contributor.author	Leopoulos, VN	en
dc.date.accessioned	2014-03-01T01:26:56Z
dc.date.available	2014-03-01T01:26:56Z
dc.date.issued	2007	en
dc.identifier.issn	17460573	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18291
dc.subject	Case study	en
dc.subject	MCS	en
dc.subject	Monte Carlo simulation	en
dc.subject	PERT	en
dc.subject	Project management	en
dc.subject	Risk management	en
dc.subject	Scheduling	en
dc.title	Project's duration prediction: Traditional tools or simulation?	en
heal.type	journalArticle	en
heal.identifier.primary	10.1504/WREMSD.2007.014049	en
heal.identifier.secondary	http://dx.doi.org/10.1504/WREMSD.2007.014049	en
heal.publicationDate	2007	en
heal.abstract	Project schedule development with CPM cannot handle uncertainty, thus PERT and Monte Carlo Simulation (MCS) are the most frequently used methods from best-in-class companies. This study compares the results of the standard MCS with those of PERT and addresses the incorporation of project risk management into the two approaches. It defines the related advantages and disadvantages, found in the literature and is illustrated through a case study. The findings reveal that the modelling of risk is more robust when the MCS is used, leading to the conclusion that simulation is a more efficient tool than the other stochastic methods. Copyright © 2007 Inderscience Enterprises Ltd.	en
heal.journalName	World Review of Entrepreneurship, Management and Sustainable Development	en
dc.identifier.doi	10.1504/WREMSD.2007.014049	en
dc.identifier.volume	3	en
dc.identifier.issue	3-4	en
dc.identifier.spage	317	en
dc.identifier.epage	333	en