|International Computer Science and Engineering Society (ICSES)|
ICSES Transactions on Neural and Fuzzy Computing
Vol. 2, No. 3, Sep. 2019
An Extension of Earned Value Technique Considering Earned Quality and Weighted Activities Under Interval Fuzzy Environment | Original Paper
Sepehr Hendiani a,, Ebrahim Sharifi b, Morteza Bagherpour c, Seyed Farid Ghannadpour d
Highlights and Novelties
This study aims at modelling the Earned Value Management (EVM) technique with weighted activities under interval fuzzy environment. The EVM has been carried out in both deterministic and uncertain conditions over the past decade. The fuzzy sets introduced first by Zadeh, also have been implemented through EVM in order to present a practical approach for evaluating performance of the projects with uncertainties. Interval type-2 Trapezoidal Fuzzy Sets is a generalized format of the conventional fuzzy sets proposed to utilize in cases where each single activity owns individual weight instead of considering same weights for all. In this paper, first, the EVM indices are remodeled using weighted IVTFS for projects, then a novel decision-making tool is proposed to determine the status of cost and schedule performances. Also, Quality Performance Index, which is recently included to the EVM as the third index, is considered as an interval-valued trapezoidal fuzzy set to demonstrate how efficient the project is able to satisfy the Quality Requirements. Finally, an illustrative case is presented to demonstrate application of the proposed model and its superiority over existing ones. The model is then validated by applying sensitivity analysis to distinguish the effect of different weights for each activity.
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors.
Cite this manuscript as
Sepehr Hendiani, Ebrahim Sharifi, Morteza Bagherpour, Seyed Farid Ghannadpour, "An Extension of Earned Value Technique Considering Earned Quality and Weighted Activities Under Interval Fuzzy Environment," ICSES Transactions on Neural and Fuzzy Computing (ITNFC), vol. 2, no. 3, pp. 16-30, Sep. 2019.
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