Predicting construction cost under uncertainty using grey-fuzzy earned value analysis

Abstract

Insufficient emphasis on planning and control is one of the major causes of several delayed and cost-overrun construction projects. To improve such performances, many studies have been conducted on project control techniques such as Earned Value Analysis (EVA) and its modifications: fuzzy EVA and grey EVA. Since there is no analytical model integrating fuzzy theory and grey theory simultaneously with EVA, this research aimed at predicting construction cost under uncertainty using grey-fuzzy EVA. Consequently, simple and valid project cost control grey-fuzzy EVA algorithms were developed to ensure continuous project cost performance improvement in the presence of imprecise data. In addition, an analysis result interpretation scheme was presented. Grey-fuzzy EVA was compared with fuzzy EVA and grey EVA to check its validity. Then, a case study of a road project in Addis Ababa, Ethiopia, was presented to demonstrate the application of grey-fuzzy EVA. This research contributes determinations of the lower limit, median, and upper limit of predicted costs and degree of greyness using grey-fuzzy EVA, which simplifies cost analysis, requires only a small number of data points (BAC, PV, AC, and Progress), needs no experts to create a membership function, and is comprehensible for practitioners as compared to fuzzy EVA and grey EVA used separately.

Keywords

• Earned value analysis
• Fuzzy theory
• Grey theory
• Uncertainty
• Grey-fuzzy EVA
• Cost control