A New Decision Support System at Estimation of Project Completion Time Considering the Combination of Artificial Intelligence Methods based on Earn Value Management Framework

Authors

  • M. H. Hajialia
  • M. R. Mosavi Iran University of Science and Technology
  • K. Shahanaghi

DOI:

https://doi.org/10.23055/ijietap.2020.27.1.2934

Abstract

One of the important issues in project management is estimation of projects completion time. This paper proposes a model based on ensemble learning using certain features of projects in Earn Value Management (EVM) to estimate project completion time. Proper simulation of the dynamic nature of the project, higher reliability in comparison with individual methods, better robustness against the presence of a weak estimator, and appropriate control of the type and number of the existing regressions in ensemble are the important features of the proposed model. The proposed method is evaluated based on two datasets, which are created by three real projects, and promising results are obtained as compared to the other well-known estimators.

Author Biography

M. R. Mosavi, Iran University of Science and Technology

Mohammad-Reza Mosavi (Corresponding Author) received his B.S., M.S., and Ph.D. degrees in Electronic Engineering from Iran University of Science and Technology (IUST), Tehran, Iran in 1997, 1998, and 2004, respectively. He is currently faculty member (full professor) of the Department of Electrical Engineering of IUST. He is the author of more than 250 scientific publications in journals and international conferences. His research interests include circuits and systems design.

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Published

2020-02-17

How to Cite

Hajialia, M. H., Mosavi, M. R., & Shahanaghi, K. (2020). A New Decision Support System at Estimation of Project Completion Time Considering the Combination of Artificial Intelligence Methods based on Earn Value Management Framework. International Journal of Industrial Engineering: Theory, Applications and Practice, 27(1). https://doi.org/10.23055/ijietap.2020.27.1.2934

Issue

Vol. 27 No. 1 (2020)

Section

Production Planning and Control

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