Fuzzy earned value management using L-R fuzzy numbers

Mortaji, Seyed Taha Hossein; Bagherpour, Morteza; Noori, Siamak

doi:10.3233/ifs-2012-0556

Cited by 23 publications

(5 citation statements)

References 21 publications

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“…Such effort is directed at improving the accuracy and reliability of the results of such forecasts [9,10]. A fuzzy approach is proposed for planning, as it enables inclusion of the uncertainty aspect of the planned activities and simultaneous use of crashing and fast tracking in the project schedule [11][12][13]. Research efforts are currently focused on finding ways to improve the accuracy of forecasting within EVM [14,15].…”

Section: Earned Value Methodsmentioning

confidence: 99%

Control of construction projects using the Earned Value Method - case study

Araszkiewicz

Bochenek

2019

Open Engineering

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Planning, controlling, monitoring progress are key management functions for effective implementation of construction projects. Commonly used instruments enabling performance of these functions include schedules and budgets, often in the form of a cost estimate. They are created at the initial planning stage to monitor and control cost and time deviations. Moreover, popular monitoring techniques are, for example, observation of milestones and comparative analysis of actual versus planned costs. This article presents a work progress control tool - the Earned Value Method (EVM) - which, despite its benefits, remains relatively unused in construction projects. The impact of the planning phase on the results obtained during the monitoring and control phase when utilizing EVM is discussed. This case study provides practical examples of using EVM in the implementation of construction projects and with the use of computer software. The novelty of the article results from the introduction of additional sensitivity analysis illustrating the impact of factors, such as an increase in costs or a change in delivery dates to the course of deviation curves. Use of sensitivity analysis in relation to the results of the CPI and SPI calculations affords combining control of costs and time with risk monitoring in the project. The findings reveal significant benefits in using EVM to implement construction projects but also highlight some important limitations.

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Section: Earned Value Methodsmentioning

confidence: 99%

Control of construction projects using the Earned Value Method - case study

Araszkiewicz

Bochenek

2019

Open Engineering

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“…In addition, the works [96,100] also presented successful cost prediction in EVM, applying fuzzy NN and SVM, respectively. What is more, Mortaji et al [107] used L-R fuzzy numbers to formulate EVM in vagueness environments for better planning, which provides efficient cost forecasting.…”

Section: Measurement Pdmentioning

confidence: 99%

Artificial Intelligence Enabled Project Management: A Systematic Literature Review

et al. 2023

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In the Industry 5.0 era, companies are leveraging the potential of cutting-edge technologies such as artificial intelligence for more efficient and green human-centric production. In a similar approach, project management would benefit from artificial intelligence in order to achieve project goals by improving project performance, and consequently, reaching higher sustainable success. In this context, this paper examines the role of artificial intelligence in emerging project management through a systematic literature review; the applications of AI techniques in the project management performance domains are presented. The results show that the number of influential publications on artificial intelligence-enabled project management has increased significantly over the last decade. The findings indicate that artificial intelligence, predominantly machine learning, can be considerably useful in the management of construction and IT projects; it is notably encouraging for enhancing the planning, measurement, and uncertainty performance domains by providing promising forecasting and decision-making capabilities.

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“…Naeni et al [38] present a fuzzy-based earned value model, in which they incorporate uncertainty from people's judgements and transform it into linguistic terms. Mortaji et al [39] employed EVM in vagueness environments using left-right (L-R) fuzzy numbers. Salari et al [40] used fuzzy techniques with EVM in financial aspects of the cost control system.…”

Section: Progress Monitoring: Evmmentioning

confidence: 99%