Volume 29, Issue 2 (IJIEPR 2018)                   IJIEPR 2018, 29(2): 0-0 | Back to browse issues page

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akhbari M. Project Time and Cost Forecasting using Monte Carlo simulation and Artificial Neural Networks. IJIEPR. 2018; 29 (2)
URL: http://ijiepr.iust.ac.ir/article-1-793-en.html
phd Department of Industrial Engineering, E-Branch, Islamic Azad University, Tehran, Iran , m_akhbari@iauec.ac.ir
Abstract:   (26 Views)
The aim of this study is to present a new method to predict project time and cost under uncertainty. Assuming that what happens in projects implementation which is expressed in the form of Earned Value Management (EVM) indicators is primarily related to the nature of randomness or unreliability, in this study, by using Monte Carlo simulation, and assuming a specific distribution for the time and cost of project activities, a significant number of predicting scenarios will be simulated. According to the data, an artificial neural network is used as efficient data mining methods to estimate the project time and cost at completion.
Full-Text [DOCX 214 kb]   (5 Downloads)    
Type of Study: Research | Subject: Project Control
Received: 2017/10/22 | Accepted: 2018/04/15 | Published: 2018/05/20

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