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Neural Computing and Applications

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28-01-2019 | Original Article

A new interval type-2 fuzzy approach for analyzing and monitoring the performance of megaprojects based on earned value analysis (with a case study)

Authors: Amin Eshghi, S. Meysam Mousavi, Vahid Mohagheghi

Published in: Neural Computing and Applications | Issue 9/2019

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Abstract

Major factors of project success include using tools of performance measurements and feedbacks. Earned value management (EVM) is a unique issue within megaprojects due to their inevitable external risks and variations. In order to improve the effectiveness and accuracy of future status estimation of megaprojects, in this paper a novel evaluation model is proposed which takes account of interval type-2 fuzzy sets (IT2FSs) to cope with uncertainty. In the proposed approach, in addition to cost and time criteria, a great deal of attention is paid for other important factors affecting project success, including quality, stakeholder satisfaction, safety and risk, which is computed from different perspectives. Moreover, to make informed decisions and to reduce uncertainty in assessment of megaprojects, key performance indicators (KPIs) are provided. Also, a new extension of multi-criteria decision-making method is introduced to weigh KPIs in future performance equations. Finally, the proposed IT2F-EVM approach is applied to control and estimate the future status of a real case study in a petro-refinery company. The results show that the approach can successfully address highly uncertain environments.

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Title: A new interval type-2 fuzzy approach for analyzing and monitoring the performance of megaprojects based on earned value analysis (with a case study)
Authors: Amin Eshghi
S. Meysam Mousavi
Vahid Mohagheghi
Publication date: 28-01-2019
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 9/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-018-04002-x

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