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Bai, Y (2007) Intelligent Painting Process Planner for Robotic Bridge Painting. Journal of Construction Engineering and Management, 133(04), 335–42.

Chang, C, Hanna, A S, Lackney, J A and Sullivan, K T (2007) Quantifying the Impact of Schedule Compression on Labor Productivity for Mechanical and Sheet Metal Contractor. Journal of Construction Engineering and Management, 133(04), 287–96.

Ko, C and Cheng, M (2007) Dynamic Prediction of Project Success Using Artificial Intelligence. Journal of Construction Engineering and Management, 133(04), 316–24.

Ling, F Y Y, Hartmann, A, Kumaraswamy, M and Dulaimi, M (2007) Influences on Innovation Benefits during Implementation: Client’s Perspective. Journal of Construction Engineering and Management, 133(04), 306–15.

Maloney, W F, Cameron, I and Hare, B (2007) Tradesmen Involvement in Health and Safety. Journal of Construction Engineering and Management, 133(04), 297–305.

Shaheen, A A, Fayek, A R and AbouRizk, S M (2007) Fuzzy Numbers in Cost Range Estimating. Journal of Construction Engineering and Management, 133(04), 325–34.

  • Type: Journal Article
  • Keywords: Fuzzy sets; Cost estimates; Monte Carlo method; Construction management;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2007)133:4(325)
  • Abstract:
    Range estimating is a simple form of simulating a project estimate by breaking the project into work packages and approximating the variables in each package using statistical distributions. This paper explores an alternate approach to range estimating that is grounded in fuzzy set theory. The approach addresses two shortcomings of Monte Carlo simulation. The first is related to the analytical difficulty associated with fitting statistical distributions to subjective data, and the second relates to the required number of simulation runs to establish a meaningful estimate of a given parameter at the end of the simulation. For applications in cost estimating, the paper demonstrates that comparable results to Monte Carlo simulation can be achieved using the fuzzy set theory approach. It presents a methodology for extracting fuzzy numbers from experts and processing the information in fuzzy range estimating analysis. It is of relevance to industry and practitioners as it provides an approach to range estimating that more closely resembles the way in which experts express themselves, making it practically easy to apply an approach.

Song, Y and Chua, D K H (2007) Temporal Logic Representation Schema for Intermediate Function. Journal of Construction Engineering and Management, 133(04), 277–86.

Vaziri, K, Carr, P G and Nozick, L K (2007) Project Planning for Construction under Uncertainty with Limited Resources. Journal of Construction Engineering and Management, 133(04), 268–76.