سال انتشار: ۱۳۸۴

محل انتشار: دومین کنفرانس بین المللی مدیریت پروژه

تعداد صفحات: ۱۵

نویسنده(ها):

Vahid Khodakarami – PhD student in Radar group Department of Computer Science Queen Mary University of London
Norman Fenton – Professor of computer Science and head of Radar group Department of Computer Science Queen Mary University of London

چکیده:

Project planning inevitably involves uncertainty. The basic input parameters for planning (time, cost and resources for each activity) are not deterministic and are affected by various sources of uncertainty. Moreover, there is a causal relationship between these uncertainty sources and project parameters; this causality is not modeled in current state-of-the-art project planning techniques (such as simulation techniques). In this paper we present an approach, using Bayesian network modelling, that addresses both uncertainty and causality in project management. Bayesian networks have been widely used in a range of decision-support applications, but the application to project management is novel. The model we present empowers the traditional Critical Path Method (CPM) to handle uncertainty and also provides explanatory analysis to elicit, represent, and manage different sources of uncertainty in project planning.