Z-Number-Based Quantitative Expression of Activity Information in Uncertain Project Scheduling

Abstract

Uncertainty is the general state of modern project scheduling, and fuzzy numbers are the main theme to resolve uncertain project scheduling problems. Traditional fuzzy numbers can represent uncertain information values of construction projects, but cannot reflect the accuracy and reliability of such information. The Z-number can express the uncertain construction project information reasonably via the first component, and use the second component to describe objectively the accuracy and reliability of information values, thus effectively overcoming the existing disadvantages of traditional fuzzy numbers. This study used historical statistical data and expert opinions to construct the Z-number, which effectively overcomes the drawbacks of conventional fuzzy numbers in disposing the uncertain activity information. A Z-number quantization scheme based on the fuzzy expected value and agreement index algorithm effectively eliminates a large amount of information loss caused by the quantization or defuzzification of the fuzzy number, and achieves the evolution and optimization from Z-numbers to AI fuzzy numbers. The objectivity of the research was ensured by fully considering the probability of completion of the activity and the risk preference of the decision makers. Numerical experimental results verified the effectiveness of the proposed method. Taken together, this study provides a new framework for exploring fuzzy logic–based solutions to the uncertain project scheduling problem, and fills the gap of Z-number-based quantitative expression of activity information in uncertain project scheduling.