Return to search

Combined Fuzzy and Probabilistic Simulation for Construction Management

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. / Construction Engineering and Management

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/731
Date11 1900
CreatorsSadeghi, Naimeh
ContributorsFayek, Aminah Robinson (Civil and Environmental Engineering), Mohamed, Yasser (Civil and Environmental Engineering), Pedrycz, Witold (Electrical and Computer Engineering)
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
Languageen_US
Detected LanguageEnglish
TypeThesis
Format8513165 bytes, application/pdf
RelationSadeghi, N. Fayek, A.R. and Pedrycz, W. (2009). "Fuzzy Monte Carlo Simulation and Risk Assessment in Construction. Accepted for publication in the journal of Computer-Aided Civil and Infrastructure Engineering, Sadeghi, N. and Fayek, A.R. (2008). A Framework for Simulating Industrial Construction Processes. Proceeding of the 2008 Winter Simulation Conference.

Page generated in 0.0017 seconds