Fuzzy Logic-Based Method for Forecasting Project Final Cost

Forecasting the final cost of construction projects during the construction phases is challenging, particularly for long-duration projects, due to the rise in uncertainties associated with future cost performance index values after report dates and the impact of many factors on cost performance. Current practices, along with existing methods and models, often assume that the cost performance index (CPI) achieved at the report date will continue as is for the remaining work and they fail to assess the risk of cost overruns. This assumption may not be true, as in many cases, the cost performance may change due to the impact of many factors. Thus, this paper aims to introduce a new multi-method fuzzy-based forecasting model to forecast the project’s final cost and to circumvent the limitations and setbacks of the used models and methods. It integrates earned value concepts with expert judgment using fuzzy logic to address the limitations of current practice in forecasting a project’s final cost during construction. Factors influencing future cost performance were identified through conducting in-depth literature reviews and expert interviews. The identified factors were then weighed using the relative importance index and pairwise comparisons. The top five most important factors are labor productivity, rework percentage, manpower availability, subcontractor management, and project plan controllability. These factors were then utilized to define the uncertainty associated with the future cost performance according to a project management team’s experience, using fuzzy numbers for forecasting the project’s final cost. Validation with real construction projects showed that the model provides more accurate predictions of completion costs through straightforward calculations. The model has been implemented in a computer application that is integrated with commercial scheduling software (P6 Professional).

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Publication Details

Journal
Buildings
Published
2024-11-24
DOI
https://doi.org/10.3390/buildings14123738
Citations
6
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
1.59

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article

Fuzzy Logic-Based Method for Forecasting Project Final Cost

Ashraf A. Bahraq, Awsan Mohammed, Mohammad A. Hassanain, Adel Alshibani et al.
6 citations
Buildings
BIM and Construction Integration
1.59
article

Fuzzy Logic-Based Method for Forecasting Project Final Cost

Ashraf A. Bahraq, Awsan Mohammed, Mohammad A. Hassanain, Adel Alshibani, Mohammed Ali Al-Osta, Badr Eddin Hafez
article en
6 citations

Abstract

Forecasting the final cost of construction projects during the construction phases is challenging, particularly for long-duration projects, due to the rise in uncertainties associated with future cost performance index values after report dates and the impact of many factors on cost performance. Current practices, along with existing methods and models, often assume that the cost performance index (CPI) achieved at the report date will continue as is for the remaining work and they fail to assess the risk of cost overruns. This assumption may not be true, as in many cases, the cost performance may change due to the impact of many factors. Thus, this paper aims to introduce a new multi-method fuzzy-based forecasting model to forecast the project’s final cost and to circumvent the limitations and setbacks of the used models and methods. It integrates earned value concepts with expert judgment using fuzzy logic to address the limitations of current practice in forecasting a project’s final cost during construction. Factors influencing future cost performance were identified through conducting in-depth literature reviews and expert interviews. The identified factors were then weighed using the relative importance index and pairwise comparisons. The top five most important factors are labor productivity, rework percentage, manpower availability, subcontractor management, and project plan controllability. These factors were then utilized to define the uncertainty associated with the future cost performance according to a project management team’s experience, using fuzzy numbers for forecasting the project’s final cost. Validation with real construction projects showed that the model provides more accurate predictions of completion costs through straightforward calculations. The model has been implemented in a computer application that is integrated with commercial scheduling software (P6 Professional).

BuildingsVol. 14(12)
King Fahd University of Petroleum and Minerals (SA)
King Fahd University of Petroleum and Minerals
Decent work and economic growth
Openalex Percentile: Top 18%
BIM and Construction Integration
1.59
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