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research-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:

S. Meysam Mousavi,

Vahid MohagheghiAuthors Info & Claims

Volume 31, Issue 9

Pages 5109 - 5133

https://doi.org/10.1007/s00521-018-04002-x

Published: 01 September 2019 Publication History

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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Cited By

Santos JPereda MAhedo VGalán J(2023)Explainable machine learning for project management controlComputers and Industrial Engineering10.1016/j.cie.2023.109261180:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.cie.2023.109261
Dai JKe D(2022)Cost Early-Warning Model System of Large-Scale Construction ProjectComputational Intelligence and Neuroscience10.1155/2022/35418032022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/3541803
Ramedani ADidehkhani HMehrabian A(2022)Scenario-based optimization robust model project portfolio selection under risk considerationsNeural Computing and Applications10.1007/s00521-022-07434-834:23(20589-20609)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s00521-022-07434-8
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A new interval type-2 fuzzy approach for analyzing and monitoring the performance of megaprojects based on earned value analysis (with a case study)

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Published In

cover image Neural Computing and Applications

Neural Computing and Applications Volume 31, Issue 9

Sep 2019

1194 pages

ISSN:0941-0643

EISSN:1433-3058

Issue’s Table of Contents

Copyright © 2019 Springer-Verlag London Ltd., part of Springer Nature.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 September 2019

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Cited By

Santos JPereda MAhedo VGalán J(2023)Explainable machine learning for project management controlComputers and Industrial Engineering10.1016/j.cie.2023.109261180:COnline publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1016/j.cie.2023.109261
Dai JKe D(2022)Cost Early-Warning Model System of Large-Scale Construction ProjectComputational Intelligence and Neuroscience10.1155/2022/35418032022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/3541803
Ramedani ADidehkhani HMehrabian A(2022)Scenario-based optimization robust model project portfolio selection under risk considerationsNeural Computing and Applications10.1007/s00521-022-07434-834:23(20589-20609)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s00521-022-07434-8
Mortaji SNoori SBagherpour M(2021)Directed earned value management based on ordered fuzzy numbersJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-20124840:5(10183-10196)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.3233/JIFS-201248
Wang MWang YChen G(2021)Interval type-2 fuzzy neural network based constrained GPC for NH flow in SCR de-NO processNeural Computing and Applications10.1007/s00521-021-06227-933:23(16057-16078)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s00521-021-06227-9
Luo GWang ZMa BWang YXu J(2021)Observer-based interval type-2 fuzzy friction modeling and compensation control for steer-by-wire systemNeural Computing and Applications10.1007/s00521-021-05801-533:16(10429-10448)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s00521-021-05801-5
Mousavi SForoozesh NZavadskas EAntucheviciene J(2020)A new soft computing approach for green supplier selection problem with interval type-2 trapezoidal fuzzy statistical group decision and avoidance of information lossSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-020-04675-424:16(12313-12327)Online publication date: 28-Jan-2020
https://dl.acm.org/doi/10.1007/s00500-020-04675-4

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