Developing realistic and unbiased simulation models for construction operations require addressing the operational and strategic decision making levels. The dynamics and feedback processes observed in construction systems are responsible for the real behavior of such systems and drive the needs for hybrid and integrated simulation tools. The dominant simulation methods such as discrete event simulation (DES) and system dynamics (SD) are limited individually of capturing all the significant construction operation aspects that are responsible for generating the behaviour of realistic models. Therefore, this thesis presents a hybrid simulation method for simulating construction operations by utilizing the joint powerful features of the DES and SD methods. 
The proposed method provides a framework to integrate DES and SD on single computational platform. Developing a hybrid simulation model commences by decomposing the construction project into units, form which simulation models (e.g. DES or SD) are developed. A unidirectional variables interaction from DES to SD models is used. The interfacing process among simulation models is achieved by defining three variables: sender, interface, and receiver. The mechanism that controls data mapping processes between variables is outlined in a new developed synchronization method. The variables interaction protocol is described using formalism. Finally, a Hybrid Simulation Application (HiSim) is coded in VB.NET to demonstrate a sequential implementation of the developed method. 
A real-world earthmoving project is modeled and simulated to test the developed hybrid simulation method. The hybrid simulation structure uses unidirectional and sequential interactions between the components of DES and SD models. The simulation is run under three scenarios, is able to predict the real project completion duration with 92% accuracy, and captures the influences of the context level variables. The findings are expected to enhance hybrid simulation applications in construction and to allow for better understanding of the impact of various internal and external factors on the project schedule and its productivity performance.