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Al-Humaidi, H M (2016) Construction Projects Bid or Not Bid Approach Using the Fuzzy Technique for Order Preference by Similarity FTOPSIS Method. Journal of Construction Engineering and Management, 142(12).
Bhaumik, P K (2016) Developing and Using a New Family of Project S-Curves Using Early and Late Shape Parameters. Journal of Construction Engineering and Management, 142(12).
Cheng, E W L (2016) Intentions to Form Project Partnering in Hong Kong: Application of the Theory of Planned Behavior. Journal of Construction Engineering and Management, 142(12).
Choi, Y S, Lim, I, Kim, T, Cho, H and Kang, K (2016) Case Study of the Core Structure Succeeding Method for Tall Building Construction. Journal of Construction Engineering and Management, 142(12).
Chong, D, Wang, Y, Chen, L and Yu, B (2016) Modeling and Validation of Energy Consumption in Asphalt Mixture Production. Journal of Construction Engineering and Management, 142(12).
Doan, D T and Chinda, T (2016) Modeling Construction and Demolition Waste Recycling Program in Bangkok: Benefit and Cost Analysis. Journal of Construction Engineering and Management, 142(12).
Elbarkouky, M M G, Fayek, A R, Siraj, N B and Sadeghi, N (2016) Fuzzy Arithmetic Risk Analysis Approach to Determine Construction Project Contingency. Journal of Construction Engineering and Management, 142(12).
Firouzi, A, Yang, W and Li, C (2016) Prediction of Total Cost of Construction Project with Dependent Cost Items. Journal of Construction Engineering and Management, 142(12).
Hassan, M E, Kandil, A, Senouci, A and Al-Derham, H (2016) Organizational Behavior Attributes and Sustainable Construction Adoption: An Econometric Analysis Using Data from Qatar. Journal of Construction Engineering and Management, 142(12).
Hyari, K H, Tarawneh, Z S and Katkhuda, H N (2016) Detection Model for Unbalanced Pricing in Construction Projects: A Risk-Based Approach. Journal of Construction Engineering and Management, 142(12).
Li, S, Cai, H and Kamat, V R (2016) Integrating Natural Language Processing and Spatial Reasoning for Utility Compliance Checking. Journal of Construction Engineering and Management, 142(12).
M. Said, H M and Lucko, G (2016) Float Types in Construction Spatial Scheduling. Journal of Construction Engineering and Management, 142(12).
Namian, M, Albert, A, Zuluaga, C M and Behm, M (2016) Role of Safety Training: Impact on Hazard Recognition and Safety Risk Perception. Journal of Construction Engineering and Management, 142(12).
Patel, D A, Kikani, K D and Jha, K N (2016) Hazard Assessment Using Consistent Fuzzy Preference Relations Approach. Journal of Construction Engineering and Management, 142(12).
Pishdad-Bozorgi, P, de la Garza, J M and Austin, R B (2016) Readiness Assessment for Flash Tracking. Journal of Construction Engineering and Management, 142(12).
Sadeghi, N, Fayek, A R and Gerami Seresht, N (2016) A Fuzzy Discrete Event Simulation Framework for Construction Applications: Improving the Simulation Time Advancement. Journal of Construction Engineering and Management, 142(12).
- Type: Journal Article
- Keywords: Construction management; Fuzzy sets; Simulation; Quantitative methods;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001195
- Abstract:
Discrete event simulation (DES) has been widely used for scheduling and analysis of construction projects. Integration of DES with fuzzy logic enhances the capabilities of DES by capturing imprecise, subjective, and linguistically expressed knowledge in the simulation inputs using fuzzy numbers. However, available fuzzy discrete event simulation (FDES) methodologies have significant shortcomings in handling fuzzy ranking and updating of the simulation time. These limitations often result in the inaccurate estimation of the start and completion times for individual activities and the whole project. This paper presents a new approach for calculating the event times to increase the accuracy of simulation time estimation in FDES. The major contributions of this paper are in integrating DES with fuzzy logic to increase its applicability in the construction domain and increasing the accuracy of FDES results. The proposed FDES approach was implemented in a construction project scheduling example, which confirms the higher accuracy of the proposed methodology compared to existing FDES methodologies.