Combined Fuzzy and Probabilistic Simulation for Construction Management

• Author / Creator

  Sadeghi, Naimeh

• Simulation has been used extensively for addressing probabilistic uncertainty in range estimating for construction projects. However, subjective and linguistically expressed information results in added non-probabilistic uncertainty in construction management. Fuzzy logic has been used successfully for representing such uncertainties in construction projects. In practice, an approach that can handle both random and fuzzy uncertainties in a risk assessment model is necessary. In this thesis, first, a Fuzzy Monte Carlo Simulation (FMCS) framework is proposed for risk analysis of construction projects. To verify the feasibility of the FMCS framework and demonstrate its main features, a cost range estimating template is developed and employed to estimate the cost of a highway overpass project. Second, a hybrid framework that considers both fuzzy and probabilistic uncertainty for discrete event simulation of construction projects is suggested. The application of the proposed framework is discussed using a real case study of a pipe spool fabrication shop.

• Subjects / Keywords

  • Range estimating
  • Industrial Construction
  • Construction management
  • Probabilistic Uncertainty
  • Monte Carlo simulation
  • Risk analysis
  • Fuzzy logic
  • Discrete event simulation
  • Pipe spool fabrication

• Graduation date

  Fall 2009

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3B635

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.